-
Notifications
You must be signed in to change notification settings - Fork 35
/
README.md.bak
323 lines (260 loc) · 37.8 KB
/
README.md.bak
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
# Awesome Conformal Prediction [](https://awesome.re)
A professionally curated list of Awesome Conformal Prediction tutorials, videos, books, papers and open-source libraries in Python and R.
Please star the repo and spread the word
Slack channel -> https://join.slack.com/t/awesomeconfor-vwn5421/shared_invite/zt-10trn4rdf-wH1w0yv9S6I5Ja~YCZT7mg
-------------------------------------------------------------------------------------------------------------------------------------------------------------------
Why Conformal Prediction?
One of the most influential and celebrated machine learning researchers - Professor Michael I. Jordan: 🔥🔥🔥🔥🔥
'𝗖𝗼𝗻𝗳𝗼𝗿𝗺𝗮𝗹 𝗣𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝗼𝗻 𝗶𝗱𝗲𝗮𝘀 𝗮𝗿𝗲 𝗧𝗛𝗘 𝗮𝗻𝘀𝘄𝗲𝗿 𝘁𝗼 𝗨𝗤 (𝘂𝗻𝗰𝗲𝗿𝘁𝗮𝗶𝗻𝘁𝘆 𝗾𝘂𝗮𝗻𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻), 𝗜 𝘁𝗵𝗶𝗻𝗸 𝗶𝘁'𝘀 𝘁𝗵𝗲 𝗯𝗲𝘀𝘁 𝗜 𝗵𝗮𝘃𝗲 𝘀𝗲𝗲𝗻 𝗶𝘁𝘀 𝘀𝗶𝗺𝗽𝗹𝗲, 𝗴𝗲𝗻𝗲𝗿𝗮𝗹𝗶𝘀𝗮𝗯𝗹𝗲 𝗲𝘁𝗰.' (ICML 2021 UQ workshop).
One the most influential statistics Professors - Larry Wasserman (Carnegie Mellon): 🚀🚀🚀🚀🚀
'I think it is a combination of things. 𝗦𝗼 𝘁𝗵𝗲 𝗯𝗲𝗮𝘂𝘁𝘆 𝗼𝗳 𝘁𝗵𝗲 𝗰𝗼𝗻𝗳𝗼𝗿𝗺𝗮𝗹 𝘁𝗵𝗶𝗻𝗴 𝗶𝘀 𝗵𝗼𝘄 𝘀𝗶𝗺𝗽𝗹𝗲 𝗶𝘁 𝗶𝘀 𝘁𝗼 𝗱𝗼 𝗶𝘁 𝗮𝗻𝗱 𝗵𝗼𝘄 𝗴𝗲𝗻𝗲𝗿𝗮𝗹 𝗶𝘁 𝗶𝘀. So I think you know ideas that catch on, general ideas that are pretty general and 𝐞𝐚𝐬𝐲 𝐭𝐨 𝐢𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭 𝐭𝐡𝐚𝐭 𝐲𝐨𝐮 𝐜𝐚𝐧 𝐩𝐢𝐜𝐭𝐮𝐫𝐞 𝐲𝐨𝐮𝐫𝐬𝐞𝐥𝐟 𝐮𝐬𝐢𝐧𝐠 𝐢𝐧 𝐫𝐞𝐚𝐥 𝐚𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 𝐚𝐫𝐞 𝐭𝐡𝐞 𝐫𝐞𝐚𝐬𝐨𝐧 𝐭𝐡𝐚𝐭 𝐩𝐞𝐨𝐩𝐥𝐞 𝐮𝐬𝐢𝐧𝐠 𝐜𝐨𝐧𝐟𝐨𝐫𝐦𝐚𝐥 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐨𝐧.'
https://slideslive.com/icml-2021/workshop-on-distributionfree-uncertainty-quantification
When both the top machine learning and the top statistic professors from the best research labs in the world say this about conformal prediction it is quite an endorsement.
-------------------------------------------------------------------------------------------------------------------------------------------------------------------
📢📢Industry take notice. The revolution in Uncertainty Quantification / Probabilistic Prediction / Forecasting is already here 📢📢 A big one 🔥🔥🔥🔥🔥
🌟 🌟 🌟 🌟 🌟
Featured resource "A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification
Anastasios N. Angelopoulos and Stephen Bates (Berkekey, December 26, 2021)." 🔥🔥🔥🔥🔥
This is newest version of the super-popular tutorial on Conformal Prediction now significantly expanded (2x), including advanced techniques such as covariate shift conformal, as well as a super fun history and lit review in S7.
https://people.eecs.berkeley.edu/~angelopoulos/publications/downloads/gentle_intro_conformal_dfuq.pdf
https://www.youtube.com/watch?v=nql000Lu_iE&t=1769s
⭐⭐️⭐️⭐️⭐️
## Table of Contents
* **[Books](#books)**
* **[PhD Theses](#theses)**
* **[Video Tutorials, Videos and Lectures](#videos)**
* **[Patents](#patents)**
* **[Papers](#papers)**
* **[Tutorials](#tutorials)**
* **[Researchers](#researchers)**
* **[Websites](#websites)**
* **[Conferences](#Conferences)**
* **[Software in Python](#software_Python)**
* **[Software in R](#software_R)**
* **[Software in Julia](#software_Julia)**
* **[Software in C++](#software_C++)**
* **[Software in Scala and Spark](#software_R)**
* **[Miscellaneous](#miscellaneous)**
* **[Contributing](#contributing)**
<a href="https://www.buymeacoffee.com/valeman" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/default-orange.png" alt="Buy Me A Coffee" height="41" width="174"></a>
### Books
1. [Algorithmic Learning in a Random World](https://link.springer.com/book/10.1007/b106715) by Vladimir Vovk and Alex Gammerman, also Glenn Shafer (2005). Second edition in progress.
2. [Conformal Prediciton for Reliable Machine Learning](https://www.elsevier.com/books/conformal-prediction-for-reliable-machine-learning/balasubramanian/978-0-12-398537-8) by Vineeth Balasubramanian, Shen-Shyang Ho, Vladimir Vovk (2014)
### PhD Theses
1. [Conformal and Venn Predictors for large, imbalanced and sparse chemoinformatics data](https://pure.royalholloway.ac.uk/portal/files/41316291/2021toccacelipphd.pdf) by Paolo Toccaceli (Royal Holloway, UK, 2021)
2. [Competitive online algorithms for probabilistic prediction](https://pure.royalholloway.ac.uk/portal/files/36216771/Thesis_Raisa.pdf) by Raisa Dzhamtyrova (Royal Holloway, UK, 2020)
3. [Conformal Prediction and Testing under On-line Compression Models](https://pure.royalholloway.ac.uk/portal/files/20318074/2014fedorovavphd.pdf) by Valentina Fedorova (Royal Holloway, UK, 2014)
4. [Adaptive Online Learning](https://pure.royalholloway.ac.uk/portal/files/17462972/adamskiy_thesis.pdf) by Dmitry Adamskiy (Royal Holloway, UK, 2013)
5. [On discovery and exploitation of temporal structure in data sets](https://pure.royalholloway.ac.uk/portal/files/24367944/Thesis.pdf) by Scarfe, Tim (Royal Holloway, UK, 2015)
6. [Black-box Security Measuring Black-box Information Leakage via Machine Learning](https://pure.royalholloway.ac.uk/portal/files/33806285/thesis_final_after_amendments.pdf) by Giovanni Cherubin (Royal Holloway, UK, 2019)
7. [Small and Large Scale Probabilistic Classifiers with Guarantees of Validity](https://pure.royalholloway.ac.uk/portal/files/30400650/2018PetejIPhd.pdf) by Ivan Petej (Royal Holloway, UK, 2019)
8. [Towards a Question Answering View of Natural Language Processing](https://pure.royalholloway.ac.uk/portal/files/35163753/Towards_a_Question_Answering_View_of_Natural_Language_Processing_3.pdf) by Zukov Gregoric, Andrej (Royal Holloway, UK, 2019)
9. [Confidence and Venn Machines and Their Applications to Proteomics](https://pure.royalholloway.ac.uk/portal/files/1402925/PhD_Thesis_Final_Dmitry_Devetyarov.pdf) by Devetyarov, Dmitry (Royal Holloway, UK, 2019)
10. [Conformal Anomaly Detection - detecting abnormanl trajectories in surveillance applications](https://www.diva-portal.org/smash/get/diva2:690997/FULLTEXT02.pdf) by Rikard Laxhammar (University of Skoeve, Sweden, 2014)
### Tutorials
1. [A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification] (https://arxiv.org/pdf/2107.07511.pdf) by Anastasios N. Angelopoulos and Stephen Bates (2021) 🔥🔥🔥🔥🔥
2. [A Tutorial on Conformal Prediction](https://www.youtube.com/watch?v=nql000Lu_iE&t=1786s) by Anastasios Angelopoulos and Stephen Bates (2021) 🔥🔥🔥🔥🔥
3. [A Tutorial on Conformal Predictive Distributions](https://www.youtube.com/watch?v=FUi5jklGvvo&t=3s) by Paolo Toccaceli (2020) 🔥🔥🔥🔥🔥
4. [Conformal Prediciton Tutorial](https://www.youtube.com/watch?v=0MsGri8nmJQ) by Henrik Linusson (2021) 🔥🔥🔥🔥🔥
5. [Henrik Linusson: Conformal Prediction](https://www.youtube.com/watch?v=lQxH-zXrOwI&t=1522s) by Henrik Linusson (2020)
6. [Predicting with Confidence - Henrik Boström](https://www.youtube.com/watch?v=eXU-64dwHmA) by Henrik Boström (2016)
7. [Venn Predictors Tutorial](https://www.youtube.com/watch?v=KsQpkjl7u1w) by Ulf Johansson, Cecilia Sönströd, Tuve Löfström, and Henrik Boström (2021)
8. [Ulf Johansson: Venn Predictors](https://www.youtube.com/watch?v=xxZOLo8wxe0&t=98s) by Ulf Johansson (2020)
9. [A Tutorial on Conformal Prediction](https://jmlr.org/papers/v9/shafer08a.html) by Glenn Shafer and Vladimir Vovk (2008) 🔥🔥🔥🔥🔥
10. [Conformal Prediction: a Unified Review of Theory and New Challenges](https://www.e-publications.org/ims/submission/BEJ/user/submissionFile/46245?confirm=193b4e5b) by Gianluca Zeni, Matteo Fontana1 and Simone Vantini (Politecnico di Milano, Italy, 2021)
### Video Tutorials, Videos and Lectures
1. [Treatment of Uncertainty in the Foundations of Probability](https://www.youtube.com/watch?v=B7E-QJ9fm4w&t=2297s) by Vladimir Vovk (Royal Holloway, UK, 2017)
2. [Large-Scale Probabilistic Prediction With and Without Validity Guarantees](https://www.youtube.com/watch?v=ksrUJdb2tA8) by Vladimir Vovk (Royal Holloway, UK, NeurIPS 2015) 🔥🔥🔥🔥🔥
3. [Conformal testing in a binary model situation](https://www.youtube.com/watch?v=RTcT4YXRdMg) by Vladimir Vovk (Royal Holloway, UK, 2021)
4. [Protected probabilistic classification](https://www.youtube.com/watch?v=MpP-3suUoLY) by Vladimir Vovk (Royal Holloway, UK, 2021)
5. [Retrain or not retrain: conformal test martingales for change-point detection](https://www.youtube.com/watch?v=4Ra5KnDEfkw&t=1s) by Vladimir Vovk (Royal Holloway, UK, 2021) 🔥🔥🔥🔥🔥
6. [A Tutorial on Conformal Prediction](https://www.youtube.com/watch?v=nql000Lu_iE&t=1786s) by Anastasios Angelopoulos and Stephen Bates (Berkeley, ICML 2021) 🔥🔥🔥🔥🔥
7. [Steps Toward Trustworthy Machine Learning](https://www.youtube.com/watch?v=2iNRSgS7-L4) by Tom Dietterich (2021)
8. [A Tutorial on Conformal Predictive Distributions](https://www.youtube.com/watch?v=FUi5jklGvvo&t=3s) by Paolo Toccaceli (Royal Holloway, UK, 2020) 🔥🔥🔥🔥🔥
9. [Conformal Prediciton Tutorial](https://www.youtube.com/watch?v=0MsGri8nmJQ) by Henrik Linusson (2021) 🔥🔥🔥🔥🔥
10. [Henrik Linusson: Conformal Prediction](https://www.youtube.com/watch?v=lQxH-zXrOwI&t=1522s) by Henrik Linusson (2020)
11. [Predicting with Confidence - Henrik Boström](https://www.youtube.com/watch?v=eXU-64dwHmA) by Henrik Boström (2016)
12. [How to increase certainty in predictive modeling](https://www.youtube.com/watch?v=fQQP84yxCRs&t=1277s) by Emmanuel Candes (Stanford, 2021) 🔥🔥🔥🔥🔥
13. [Recent Progress in Predictive Inference](https://www.youtube.com/watch?v=tY73G_UvkAE&t=833s) by Emmanuel Candes (Stanford, 2020) 🔥🔥🔥🔥🔥
14. [Some recent progress in predictive inference" (Stanford) @ MAD+](https://www.youtube.com/watch?v=djgxwpJQyAA) by Emmanuel Candes (Stanford, 2020)
15. [Conformal Prediciton in 2020](https://www.youtube.com/watch?v=61tpigfLHso&t=1507s) by Emmanuel Candes (Stanford, 2020) 🔥🔥🔥🔥🔥
16. [Assumption-free prediction intervals for black-box regression algorithms](https://www.youtube.com/watch?v=GMnCO7_HIOY&t=3943s) by Aaditya Ramdas (Carnegie Mellon, 2020) 🔥🔥🔥🔥🔥
17. [Maria Navarro: Quantifying uncertainty in Machine Learning predictions | PyData London 2019](https://www.youtube.com/watch?v=r6bhm_A-YcQ&t=12s) by Maria Navarro (2019)
18. [Conformal Prediction: Enhanced Method for Understanding the Prediction Quality](https://www.youtube.com/watch?v=_ZVuEWEfwuw&t=948s) by Artem Ryasik and Greg Landrum
19. [Venn Predictors Tutorial](https://www.youtube.com/watch?v=KsQpkjl7u1w) by Ulf Johansson, Cecilia Sönströd, Tuwe Löfström, and Henrik Boström (2021)
20. [Mondrian conformal predictive distributions](https://www.youtube.com/watch?v=dHNZxw8WQrs) by Henrik Boström, Ulf Johansson, and Tuwe Löfström (2021) 🔥🔥🔥🔥🔥
21. [Calibrating Multi-Class Models](https://www.youtube.com/watch?v=uCnFgTjUYto) by Ulf Johansson, Tuwe Löfström, and Henrik Boström (2021)
22. [Conformal testing in a binary model situation](https://www.youtube.com/watch?v=RTcT4YXRdMg) by Vladimir Vovk (Royal Holloway, UK, 2021)
23. [Conformal prediction in Orange](https://www.youtube.com/watch?v=qI1jOEour1g&t=14s) by Tomaž Hočevar and Blaž Zupan (2021)
24. [Distribution-Free, Risk-Controlling Prediction Sets](https://www.youtube.com/watch?v=ITJAR3fcNuI) by Anastasios Angelopoulos (Stanford, 2021) 🔥🔥🔥🔥🔥
25. [Conformal Prediction and Distribution-Free Calibration](https://synapse.math.univ-toulouse.fr/s/KDcWmmU9j9zk0rm) by Aaditya Ramdas (Carnegie Mellon, 2021) 🔥🔥🔥🔥🔥
26. [Reliable Diagnostics by Conformal Predictors](https://www.youtube.com/watch?v=zW3R-vbLw58) by Alexander Gammerman (Royal Holloway, UK, 2015)
27. [Distribution-Free, Risk-Controlling Prediction Sets](https://www.youtube.com/watch?v=ITJAR3fcNuI) by Anastasios Angelopoulos (Stanford, 2021) 🔥🔥🔥🔥🔥
28. [Conformal Inference of Counterfactuals and Time-to-event Outcomes](https://www.youtube.com/watch?v=nfD3mrSefbI) by Lihua Lei (Stanford, 2021)
29. [Algo Hour – Conformal Inference of Counterfactuals and Individual Treatment Effect](https://www.youtube.com/watch?v=COW2QNBmEMw) by Lihua Lei (Stanford, 2021)
30. [Conformal Inference of Counterfactuals and Individual Treatment effects(Stanford)](https://www.youtube.com/watch?v=8tM4BhONHms) by Lihua Lei (Stanford, 2021)
31. [Approximation to object conditional validity with inductive conformal predictors](https://www.youtube.com/watch?v=pUf7z2vxdi8) by Anthony Bellotti (University of Nottingham Ningbo, China, 2021)
32. [Ulf Johansson: Venn Predictors](https://www.youtube.com/watch?v=xxZOLo8wxe0&t=40s) by Ulf Johansson (Jönköping University, Sweden, 2021) 🔥🔥🔥🔥🔥
33. [Transformer-based conformal predictors for paraphrase detection](https://www.youtube.com/watch?v=HYP1ypxywWo) by Patrizio Giavannotti and Prof. Alexander Gammerman (Royal Holloway, UK, 2021)
34. [Conformal Inference of Counterfactuals and Individual Treatment Effects](https://www.youtube.com/watch?v=jkFs6pLZXBQ) by Lihua Lei (Stanford, 2020)
35. [Model-Free Predictive Inference](https://www.youtube.com/watch?v=8GkhRuWcd0w) by Larry Wasserman (Carnegie Mellon, 2020) 🔥🔥🔥🔥🔥
36. [Shapley-value based inductive conformal prediction](https://www.youtube.com/watch?v=6XUc3HFa_5Q&t=1094s) by William Lopez Jaramillo (2021)
37. [Conformal Training: Learning Optimal Conformal Classifiers | DeepMind](https://www.youtube.com/watch?v=XMa1glDpVtQ&t=318s) by David Stutz (2021) 🔥🔥🔥🔥🔥
38. [Distribution-Free, Risk-Controlling Prediction Sets](https://www.youtube.com/watch?v=z8WDmD5D-I0) by Anastasios Angelopoulos (2021) 🔥🔥🔥🔥🔥
39. [Assumption-Free, High-Dimensional Inference](https://www.youtube.com/watch?v=UOMvUaYfpH4) by Larry Wasserman (2016)
40. [Neural Predictive Monitoring under Partial Observability](https://www.youtube.com/watch?v=JhJXUDPoKCc) by Francesca Cairolli (2021)
41. [Conformalized Kernel Ridge Regression and Its Efficiency](https://www.youtube.com/watch?v=OLeu9TXE5n4) by Evgeny Burnaev (Skolkovo, Russia, 2015)
42. [Fast conformal classification using influence functions](https://www.youtube.com/watch?v=LRwm976poDE) by Giovanni Cherubin (Alan Turing Institute, UK, 2021)
43. [Valid inferential models and conformal prediction](https://www.youtube.com/watch?v=egrLw0CmXTs) by Ryan Martin (North Carolina State University, USA, 2021)
44. [Mondrian conformal predictive distributions](https://www.youtube.com/watch?v=dHNZxw8WQrs&t=1415s) by Henrik Boström, Ulf Johansson and Tuwe Löfström (KTH Royal Institute of Technology, Sweden, 2021) 🔥🔥🔥🔥🔥
45. [Evaluation of updating strategies for conformal predictive systems in the presence of extreme events](https://www.youtube.com/watch?v=Xgs0JqDw8lA) by Hugo Werner, Lars Carlsson, Ernst Ahlberg and and Henrik Boström (KTH Royal Institute of Technology, Sweden, 2021)
46. [Exact and Robust Conformal Inference Methods for Predictive Machine Learning With Dependent Data](https://www.youtube.com/watch?v=Wcm9Uw0YL8A) by Victor Chernozhukov (MIT, USA, 2019) 🔥🔥🔥🔥🔥
47. [Ulf Johansson: Venn Predictors](https://www.youtube.com/watch?v=xxZOLo8wxe0&t=98s) by Ulf Johansson (Jönköping University, Sweden, 2020) 🔥🔥🔥🔥🔥
48. [Class-wise confidence for debt prediction in real estate management](https://www.youtube.com/watch?v=ZVhA8LGXWpc) by Soundouss Messoudi (2021)
49. [How Nonconformity Functions and Difficulty of Datasets Impact the Efficiency of Conformal Classifiers](https://www.youtube.com/watch?v=lLtZkVwxMNw) by Marharyta Aleksandrova (2021)
50. [Nested conformal prediction and quantile out-of-bag ensemble methods](https://www.youtube.com/watch?v=NlUlelNWVMQ) by Chirag Gupta (Carnegie Mellon, 2020) 🔥🔥🔥🔥🔥
52. [Panel with Michael I. Jordan, Vladimir Vovk, and Larry Wasserman, moderated by Aaditya Ramdas](https://slideslive.com/38964850/panel-with-michael-i-jordan-vladimir-vovk-and-larry-wasserman-moderated-by-aaditya-ramdas?ref=account-folder-87373-folders) by Vladimir Vovk, Larry Wasserman, Michael I. Jordan, Aaditya Ramdas, ICML 2021 🔥🔥🔥🔥🔥 🔥🔥🔥🔥🔥
53. [Black-box uncertainty - Anastasios Angelopoulos](https://www.youtube.com/watch?v=jW-mbsVgcIc) by Anastasios Angelopoulos (Berkeley, USA, 2021) 🔥🔥🔥🔥🔥
54. [P.C. Mahalanobis Memorial Lectures 2020-21](https://www.isibang.ac.in/~statmath/pcm2020/) by Vladimir Vovk (Royal Holloway, UK, 2021)
55. [Rahul Vishwakarma: New Perspective on Machine Learning Predictions Under Uncertainty | SNIA Storage Developer Conference, Santa Clara 2019](https://www.youtube.com/watch?v=T-hG1JyAk4E) by Rahul Vishwakarma (2019)
### Patents
1. [Rahul Vishwakarma, Method and system for reliably forecasting storage disk failure. US 2021/0034450 A1, United States Patent and Trademark Office, 4 February 2021](https://patentimages.storage.googleapis.com/f4/19/3d/2bca26b6be5fff/US20210034450A1.pdf)
2. [Rahul Vishwakarma, Analyzing Time Series Data for Sets of Devices Using Machine Learning Techniques. US 2021/0241929 A1, United States Patent and Trademark Office, 5 August 2021](https://patentimages.storage.googleapis.com/4f/78/2f/3a63fc5e07a083/US20210241929A1.pdf)
3. [Rahul Vishwakarma, System and method for prioritizing and preventing backup failures. US 2021/0374568 A1, United States Patent and Trademark Office, 2 December 2021](https://patentimages.storage.googleapis.com/8e/65/c3/69d60220a9e421/US20210374568A1.pdf)
### Papers
1. [Introducing Conformal Prediction in Predictive Modeling. A Transparent and Flexible Alternative to Applicability Domain Determination](https://pubs.acs.org/doi/10.1021/ci5001168) by Ulf Norinder, Lars Carlsson, Scott Boyer, and Martin Eklund (2014)
2. [Uncertainty Sets for Image Classifiers using Conformal Prediction](https://arxiv.org/pdf/2009.14193.pdf) by Anastasios N. Angelopoulos, Stephen Bates, Jitendra Malik, & Michael I. Jordan (Berkeley, 2021) 🔥🔥🔥🔥🔥
3. [Conformal Prediction Under Covariate Shift](https://arxiv.org/abs/1904.06019) by Ryan Tibshirani, Rina Foygel Barber, Emmanuel Candes, Aaditya Ramdas (Carnegie Mellon, Stanford, Chicago, 2019) 🔥🔥🔥🔥🔥
4. [Regression Conformal Prediction with Nearest Neighbours](https://arxiv.org/pdf/1401.3880.pdf) by Harris Papadopoulos, Vladimir Vovk and Alex Gammerman (Royal Holloway, UK, 2014)
5. [Nested conformal prediction and quantile out-of-bag ensemble methods](https://arxiv.org/pdf/1910.10562.pdf) by Chirag Gupta, Arun Kuchibhotla and Aaditya Ramdas (Carnegie Mellon, 2021) 🔥🔥🔥🔥🔥
6. [Cross-conformal predictive distributions](http://proceedings.mlr.press/v91/vovk18a.html) by Vladimir Vovk, Ilia Nouretdinov, Valery Manokhin and Alexander Gammerman (Royal Holloway, UK, 2018) 🔥🔥🔥🔥🔥 🔥🔥🔥🔥🔥
7. [Criteria of Efficiency for Conformal Prediction](https://arxiv.org/pdf/1603.04416.pdf) by Vladimir Vovk, Ilia Nouretdinov, Valentina Fedorova,
Ivan Petej, and Alex Gammerman ((Royal Holloway, UK, 2016)
7. [Conformal Prediction for Simulation Models](https://benjaminleroy.github.io/documents/icml2021/conformal_prediction_for_simulation_models.pdf) by Benjamin LeRoy and Chad Schafer (Carnegie Mellon, 2021)
8. [Distribution-free, risk-controlling prediction sets](https://arxiv.org/pdf/2101.02703) Stephen Bates, Anastasios Angelopoulos, Lihua Lei, Jitendra Malik and Michael I Jordan (Berkeley, 2021) 🔥🔥🔥🔥🔥
9. [Conditional calibration for false discovery rate control under dependence](https://arxiv.org/abs/2007.10438) by William Fithian and Lihua Lei (Stanford, 2021)
10. [Conformal Prediction: a Unified Review of Theory and New Challenges](https://www.e-publications.org/ims/submission/BEJ/user/submissionFile/46245?confirm=193b4e5b) by Gianluca Zeni, Matteo Fontana and S. Vantini (2021) 🔥🔥🔥🔥🔥
11. [Regression conformal prediction with random forests](https://link.springer.com/content/pdf/10.1007%2Fs10994-014-5453-0.pdf) by Ulf Johansson, Henrik Boström, Tuve Löfström and Henrik Linusson (2014)
12. [A conformal prediction approach to explore functional data](https://arxiv.org/pdf/1302.6452.pdf) by Jing Lei, Alessandro Rinaldo, Larry Wasserman (Carnegie Mellon, 2013)
13. [An electronic nose-based assistive diagnostic prototype for lung cancer detection with conformal prediction](https://pure.royalholloway.ac.uk/portal/files/37171406/Measurement_Manuscript_unmarked_R4.pdf) by Xianghao Zhana,c, Zhan Wanga, Meng Yangb, Zhiyuan Luod, You Wanga, Guang Li (2020)
14. [Predicting the Rate of Skin Penetration Using an Aggregated Conformal Prediction Framework](https://pubmed.ncbi.nlm.nih.gov/28335598/) by Martin Lindh, A. Karlén, Ulf Norinder (2017)
15. [The application of conformal prediction to the drug discovery process](https://link.springer.com/article/10.1007%2Fs10472-013-9378-2) by Martin Eklund, Ulf Norinder, Scott Boyer & Lars Carlsson (2014) 🔥🔥🔥🔥🔥
16. [Distributional conformal prediction](https://arxiv.org/pdf/1909.07889.pdf) by Victor Chernozhukov, Kaspar Wüthrich, Yinchu Zhu (2021) 🔥🔥🔥🔥🔥
17. [Anomaly Detection of Trajectories with Kernel Density Estimation by Conformal Prediction](https://link.springer.com/content/pdf/10.1007%2F978-3-662-44722-2_29.pdf) by James Smith, Ilia Nouretdinov, Rachel Craddock, Charles Offer, and Alexander Gammerman (2009)
18. [Conformal prediction interval estimation and applications to day-ahead and intraday power markets](https://arxiv.org/pdf/1905.07886.pdf) by Christopher Kath, Florian Ziel (2019) 🔥🔥🔥🔥🔥
19. [The application of conformal prediction to the drug discovery process](https://link.springer.com/article/10.1007%2Fs10472-013-9378-2) by Martin Eklund, Ulf Norinder, Scott Boyer & Lars Carlsson (2013)
20. [Anomaly Detection of Trajectories with Kernel Density Estimation by Conformal Prediction](https://link.springer.com/chapter/10.1007%2F978-3-662-44722-2_29) by James Smith, Ilia Nouretdinov, Rachel Craddock, Charles Offer, Alexander Gammerman (Royal Holloway, UK, 2014)
21. [Conformal Prediction: a Unified Review of Theory and New Challenges](https://www.e-publications.org/ims/submission/BEJ/user/submissionFile/46245?confirm=193b4e5b) by Gianluca Zeni, Matteo Fontana1 and Simone Vantini (Politecnico di Milano, Italy, 2021)
22. [Exchangeability, Conformal Prediction, and Rank Tests](https://arxiv.org/pdf/2005.06095.pdf) by Arun Kuchibhotla (Carnegie Mellon, 2021)
23. [Conformal prediction with localization](https://arxiv.org/pdf/1908.08558.pdf) by Leying Guan (Yale, 2020)
24. [Predicting skin sensitizers with confidence - Using conformal prediction to determine applicability domain of GARD](https://pubmed.ncbi.nlm.nih.gov/29374571/) by Andy Forreryd, Ulf Norinder, Tim Lindberg, Malin Lindstedt (2018)
25. [Binary classification of imbalanced datasets using conformal prediction](https://pubmed.ncbi.nlm.nih.gov/28135672/) by
Ulf Norinder, Scott Boyer (2017)
26. [Discretized conformal prediction for efficient distribution-free inference](https://arxiv.org/pdf/1709.06233.pdf) by Wenyu Chen, Kelli-Jean Chun, and Rina Foygel Barber (2017)
27. [Validity, consonant plausibility measures, and conformal prediction](https://www.sciencedirect.com/science/article/abs/pii/S0888613X21001195?via%3Dihub) by Leonardo Cella. and Ryan Martin (2021)
28. [Conformal Prediction Classification of a Large Data Set of Environmental Chemicals from ToxCast and Tox21 Estrogen Receptor Assays](https://pubmed.ncbi.nlm.nih.gov/27152554/) by Ulf Norinder, Scott Boyer (2016)
29. [Conformal prediction to define applicability domain – A case study on predicting ER and AR binding](https://www.tandfonline.com/doi/full/10.1080/1062936X.2016.1172665) by U. Norinder, A. Rybacka, P.Andersson (2016)
30. [Conformal prediction of biological activity of chemical compounds](https://link.springer.com/article/10.1007%2Fs10472-017-9556-8) by Paolo Toccaceli, Ilia Nouretdinov, Alex Gammerman (Royal Holloway, UK, 2017) 🔥🔥🔥🔥🔥
31. [Introducing conformal prediction in predictive modeling for regulatory purposes. A transparent and flexible alternative to applicability domain determination](https://pubmed.ncbi.nlm.nih.gov/25559551/) by Ulf Norinder, Lars Carlsson, Scott Boyer, Martin Eklund (2015)
32. [Aggregated Conformal Prediction](https://link.springer.com/chapter/10.1007%2F978-3-662-44722-2_25) by Lars CarlssonMartin EklundUlf Norinder (2014)
33. [Interpretation of Conformal Prediction Classification Models](https://link.springer.com/chapter/10.1007%2F978-3-319-17091-6_27) by Ernst Ahlberg, Ola Spjuth, Catrin Hasselgren, Lars Carlsson (2015)
34. [Cross-Conformal Prediction with Ridge Regression](https://link.springer.com/chapter/10.1007%2F978-3-319-17091-6_21) by Harris Papadopoulos (2015)
35. [Sparse conformal prediction for dissimilarity data](https://link.springer.com/article/10.1007%2Fs10472-014-9402-1) by Frank-Michael Schleif, Xibin Zhu and Barbara Hammer (2015)
36. [Effective utilization of data in inductive conformal prediction using ensembles of neural networks](https://ieeexplore.ieee.org/document/6706817) by Tuve Löfström, Ulf Johansson and Henrik Boström (2013)
37. [Beyond the Basic Conformal Prediction Framework](https://www.sciencedirect.com/science/article/pii/B978012398537800002X?via%3Dihub) by Vladimir Vovk (2014)
38. [An electronic nose-based assistive diagnostic prototype for lung cancer detection with conformal prediction](https://pure.royalholloway.ac.uk/portal/files/37171406/Measurement_Manuscript_unmarked_R4.pdf) by Xianghao Zhan, Zhan Wang, Meng Yang, Zhiyuan Luo, You Wang, Guang Li (Stanford, Royal Holloway, China University of Mining and Technology, 2020)
39. [Predicting with confidence: Using conformal prediction in drug discovery](https://pubmed.ncbi.nlm.nih.gov/33075380/) by Jonathan Alvarsson, Staffan Arvidsson McShane, Ulf Norinder, Ola Spjuth (2017)
40. [Inductive conformal prediction for silent speech recognition](https://pubmed.ncbi.nlm.nih.gov/32120355/) by Ming Zhang, You Wang, Zhang Wei, Meng Yang, Zhiyuan Luo, Guang Li (2020)
41. [Large scale comparison of QSAR and conformal prediction methods and their applications in drug discovery](https://jcheminf.biomedcentral.com/articles/10.1186/s13321-018-0325-4) by Nicolas Bosc, Francis Atkinson, Eloy Felix, Anna Gaulton, Anne Hersey and Andrew R. Leach (2019)
42. [Deep Conformal Prediction for Robust Models](https://link.springer.com/chapter/10.1007%2F978-3-030-50146-4_39) by Soundouss Messoudi, Sylvain Rousseau and Sébastien Destercke (2020)
43. [Strong validity, consonance, and conformal prediction](https://arxiv.org/abs/2001.09225) by Leonardo Cella and Ryan Martin (2020)
44. [Skin Doctor CP: Conformal Prediction of the Skin Sensitization Potential of Small Organic Molecules](https://pubs.acs.org/doi/10.1021/acs.chemrestox.0c00253) by Anke Wilm, U. Norinder, M. Agea, Christina de Bruyn Kops, Conrad Stork, J. Kühnl, J. Kirchmair (2020)
47. [Conformal prediction based active learning by linear regression optimization](https://www.sciencedirect.com/science/article/abs/pii/S0925231220300461?via%3Dihub) by Sergio Matiz, Kenneth E.Barner (2020)
48. [Conformal prediction intervals for the individual treatment effect](https://arxiv.org/pdf/2006.01474.pdf) by Danijel Kivaranovic, Robin Ristl, Martin Poschb, Hannes Leeb (2020)
49. [Nearest neighbor based conformal prediction](https://www.f08.uni-stuttgart.de/.content/media/downloads/Mathematik/mathematische_berichte/2020/2020-002.pdf) by László Györfi and Harro Walk (2020)
50. [Concepts and Applications of Conformal Prediction in Computational Drug Discovery](https://arxiv.org/pdf/1908.03569.pdf) by Isidro Cortés-Ciriano and Andreas Bender (2019) 🔥🔥🔥🔥🔥
51. [Predicting Ames Mutagenicity Using Conformal Prediction in the Ames/QSAR International Challenge Project](https://academic.oup.com/mutage/article/34/1/33/5239859) by Ulf Norinder, Ernst Ahlberg, Lars Carlsson (2018)
52. [Nested Conformal Prediction and the Generalized Jackknife](https://arxiv.org/pdf/1910.10562v1.pdf) by Arun Kuchibhotla and Aaditya Ramdas (Carnegie Mellon, 2019)
53. [Predictive inference with the jackknife+](https://arxiv.org/abs/1905.02928) by Rina Foygel Barber, Emmanuel Candès, Aaditya Ramdas, and Ryan Tibshirani (2020) 🔥🔥🔥🔥🔥
54. [Nonparametric predictive distributions based on conformal prediction](https://link.springer.com/article/10.1007%2Fs10994-018-5755-8) by Vladimir Vovk, Jieli Shen, Valery Manokhin and Min-ge Xie (Royal Holloway, UK, Rutgers, USA, 2018) 🔥🔥🔥🔥🔥
55. [A Distribution-Free Test of Covariate Shift Using Conformal Prediction](https://arxiv.org/pdf/2010.07147.pdf) by Xiaoyu Hu and Jing Lei (Peking Univerity, China and Carnegie Mellon, USA, 2020) 🔥🔥🔥🔥🔥
56. [Exchangeability, Conformal Prediction, and Rank Tests](https://arxiv.org/pdf/2005.06095.pdf) by Arun Kuchibhotla (Carnegie Mellon, 2021)
57. [Conformal prediction with localization](https://arxiv.org/pdf/1908.08558.pdf) by Leying Guan (2020)
58. [Multitask Modeling with Confidence Using Matrix Factorization and Conformal Prediction](https://pubmed.ncbi.nlm.nih.gov/30908915/) by Ulf Norinder, Fredrik Svensson
59. [Conformal prediction of HDAC inhibitors](https://www.tandfonline.com/doi/abs/10.1080/1062936X.2019.1591503?journalCode=gsar20) by U. Norinder, J.J.Navaka, E. Lopez-Lopez, D. Mucs & J.L. Medina-Franco (2019)
60. [Computing Full Conformal Prediction Set with Approximate Homotopy](https://arxiv.org/pdf/1909.09365.pdf) by Eugene Ndiaye, Ichiro Takeuchi (2019)
61. [Conformal Prediction Based on Raman Spectra for the Classification of Chinese Liquors](https://journals.sagepub.com/doi/10.1177/0003702819831017) by
Jiao Gu, Huaibo Liu, Chaoqun Ma, Lei Li, Chun Zhu, Christ Glorieux, Guoqing Chen (2019)
60. [Efficient and minimal length parametric conformal prediction regions](https://export.arxiv.org/pdf/1905.03657) by Daniel Eck and Forrest Crawford (2019)
61. [Conformal Prediction for Students' Grades in a Course Recommender System](http://proceedings.mlr.press/v105/morsomme19a/morsomme19a.pdf) by Raphael Morsomme and Evgueni Smirnov (2019)
62. [Efficient iterative virtual screening with Apache Spark and conformal prediction](https://jcheminf.biomedcentral.com/articles/10.1186/s13321-018-0265-z) by Laeeq Ahmed, Valentin Georgiev, Marco Capuccini, Salman Toor, Wesley Schaal, Erwin Laure and Ola Spjuth (2018)
63. [Predicting Off-Target Binding Profiles With Confidence Using Conformal Prediction](https://pubmed.ncbi.nlm.nih.gov/30459617/) by Samuel Lampa, Jonathan Alvarsson, Staffan Arvidsson Mc Shane, Arvid Berg, Ernst Ahlberg, Ola Spjuth (2018)
64. [Maximizing gain in high-throughput screening using conformal prediction](https://jcheminf.biomedcentral.com/track/pdf/10.1186/s13321-018-0260-4.pdf) by Fredrik Svensson, Avid M. Afzal1, Ulf Norinder and Andreas Bender (2018)
65. [Conformalized Survival Analysis](https://arxiv.org/pdf/2103.09763.pdf) by Emmanuel Candès, Lihua Lei and Zhimei Ren (2021) 🔥🔥🔥🔥🔥
66. [Random Forest Prediction Intervals](https://haozhestat.github.io/files/manuscript_RFIntervals_FinalVersion.pdf) by Haozhe Zhang†, Joshua Zimmerman†, Dan Nettleton† and Daniel J. Nordman† (Iowa State University, USA, 2019)
67. [Conformal Training: Learning Optimal Conformal Classifiers | DeepMind](https://arxiv.org/pdf/2110.09192.pdf) by David Stutz (DeepMind), Krishnamurthy Dvijotham, Ali Taylan Cemgil and Arnaud Doucet (2021)
68. [Comparing the Bayes and typicalness frameworks](https://link.springer.com/content/pdf/10.1007%2F3-540-44795-4_31.pdf) by Thomas Melluish, Craig Saunders, Ilia Nouretdinov, and Volodya Vovk (Royal Holloway, UK, 2001). 🔥🔥🔥🔥🔥
69. [Large-scale probabilistic predictors with and without guarantees of validity](https://papers.nips.cc/paper/2015/file/a9a1d5317a33ae8cef33961c34144f84-Paper.pdf) by Vladimir Vovk, Ivan Petej, and Valentina Fedorova (Royal Holloway, Yandex, NeurIPS) 🔥🔥🔥🔥🔥
### Researchers
1. [Vladimir Vovk](vovk.net), Royal Holloway, United Kingdom
2. [Alexander Gammerman](https://cml.rhul.ac.uk/people/alex/), Royal Holloway, United Kingdom
3. [Glenn Shafer](http://www.glennshafer.com), Rutgers University, USA
4. [Emmanuel Candès](https://candes.su.domains), Stanford, USA
5. [Ryan Tibshiriani](https://www.stat.cmu.edu/~ryantibs/), Carnegie Mellon, USA
6. [Yaniv Romano](https://sites.google.com/view/yaniv-romano/), Technion—Israel Institute of Technology
7. [Michael I. Jordan](https://people.eecs.berkeley.edu/~jordan/), Berkeley, USA
8. [Jitendra Malik](https://people.eecs.berkeley.edu/~malik/), Berkeley, USA
9. [Anastasios Angelopoulos](https://people.eecs.berkeley.edu/~angelopoulos/), Berkeley, USA
10. [Lihua Lei](https://lihualei71.github.io), Stanford, USA
11. [Henrik Boström](https://www.kth.se/profile/henbos), KTH, Sweden
12. [Ulf Johansson](https://scholar.google.com/citations?user=OZjCgIsAAAAJ&hl=en), Jönköping University, Sweden
13. [Henrik Linusson](https://scholar.google.se/citations?user=Xl8W39cAAAAJ&hl=en), University of Borås, Sweden
14. [Harris Papadopoulos](http://staff.fit.ac.cy/com.ph/), Frederick University, Cyprus
15. [Vladimir V'yugin](http://iitp.ru/ru/users/125.htm), Institute for Information Transmission Problems (IITP), Russia
16. [Evgeny Burnaev](https://faculty.skoltech.ru/people/evgenyburnaev), Skoltech, Russia
17. [Aaditya Ramdas](http://stat.cmu.edu/~aramdas/), Carnegie Mellon, USA
18. [Benjamin LeRoy](https://benjaminleroy.github.io), Carnegie Mellon, USA
19. [Victor Chernozhukov](https://www.mit.edu/~vchern/), MIT, USA
20. [Ulf Norinder](https://scholar.google.com/citations?user=i5hUEFwAAAAJ&hl=en), Stockholm University, Sweden
21. [Ola Spjuth](https://pharmb.io), Uppsala University, Sweden
22. [Ilia Nouretdinov](https://cml.rhul.ac.uk/people/nouretdinov/index.htm), Royal Holloway, United Kingdom
### Websites
1. [Main website with research from Prof. Vladimir (Volodya) Vovk](http://alrw.net) 🔥🔥🔥🔥🔥
2. [Conformal Prediction - Prediction with guaranteed performance](https://cml.rhul.ac.uk/cp.html) Royal Holloway, United Kingdom
3. [A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification](https://people.eecs.berkeley.edu/~angelopoulos/blog/posts/gentle-intro/) by Anastasios N. Angelopoulos 🔥🔥🔥🔥🔥
4. [Reliable Predictive Inference](https://sites.google.com/view/cqr) by Yaniv Romano 🔥🔥🔥🔥🔥
### Conferences
1. https://icml.cc/Conferences/2021/ScheduleMultitrack?event=8373 🔥🔥🔥🔥🔥
2. https://cml.rhul.ac.uk/copa2021/ 🔥🔥🔥🔥🔥
3. https://cml.rhul.ac.uk/copa2020/ 🔥🔥🔥🔥🔥
4. https://cml.rhul.ac.uk/copa2019/ 🔥🔥🔥🔥🔥
5. https://cml.rhul.ac.uk/copa2018/ 🔥🔥🔥🔥🔥
6. https://cml.rhul.ac.uk/copa2017/ 🔥🔥🔥🔥🔥
### Software Python
1. [Nonconformist](https://github.com/donlnz/nonconformist) by Henrik Linusson (2015) 🔥🔥🔥🔥🔥
2. [Venn-ABERS Predictor](https://github.com/ptocca/VennABERS) by Paolo Toccaceli (2019), based on NeurIPS 2015 paper 'Large-scale probabilistic predictors with and without guarantees of validity' (#69 on papers list) 🔥🔥🔥🔥🔥
3. [MAPIE - Model Agnostic Prediction Interval Estimator](https://github.com/scikit-learn-contrib/MAPIE) (2021) 🔥🔥🔥🔥🔥
4. ['Crêpes' - Conformal regressors and predictive systems](https://github.com/henrikbostrom/crepes) by Henrik Boström (2021)
5. [Conformalized Quantile Regression](https://github.com/yromano/cqr) by Yaniv Romano (2019) 🔥🔥🔥🔥🔥
6. [Conformal Classification](https://github.com/aangelopoulos/conformal_classification) by Anastasios N. Angelopoulos (2021)
7. [Orange3 Conformal Prediction](https://github.com/biolab/orange3-conformal)
8. [EnbPI](https://github.com/hamrel-cxu/EnbPI) by Chen Xu (2021)
9. [Conformal: an R package to calculate prediction errors in the conformal prediction framework](https://github.com/isidroc/conformal/) by Isidro Cortes, 2019
10. [Copula Conformal Multi Target Regression](https://github.com/M-Soundouss/CopulaConformalMTR) by Soundouss Messoudi (2021)
11. [Uncertainty Toolbox](https://github.com/uncertainty-toolbox/uncertainty-toolbox) by Youngseog Chung, Willie Neiswanger, Ian Char and Han Guo (2021)
### Software R
1. [Conformal Inference R Project](https://github.com/ryantibs/conformal) maintained by Ryan Tibshirani (2016) 🔥🔥🔥🔥🔥
2. [Prediction Bands](https://github.com/rizbicki/predictionBands) by Rafael Izbicki and Benjamin LeRoy (2019)
3. [Conformal: an R package to calculate prediction errors in the conformal prediction framework](https://github.com/isidroc/conformal/) by Isidro Cortes, 2019
4. [Online Time Series Anomaly Detectors](https://github.com/valeman/otsad) by Alaine Iturria, 2021 🔥🔥🔥🔥🔥
5. [piRF - Prediction Intervals for Random Forests](https://github.com/chancejohnstone/piRF) by Chancellor Johnstone and Haozhe Zhang (2019)
6. [conformalClassification: Transductive and Inductive Conformal Predictions for Classification Problems](https://cran.r-project.org/web/packages/conformalClassification/) by Niharika Gauraha and Ola Spjuth (2019)
### Software C++
1. [LibCP -- A Library for Conformal Prediction](https://github.com/fated/libcp) 🔥🔥🔥🔥🔥
2. [An Implementation of Venn-ABERS predictor](https://github.com/fated/venn-abers-predictor) 🔥🔥🔥🔥🔥
3. [LibVM -- A Library for Venn Machine](https://github.com/fated/libvm)
### Software Julia
1. [RandomForest](https://github.com/henrikbostrom/RandomForest) by Henrik Boström (2017) 🔥🔥🔥🔥🔥
### Software Scala and Spark
[Scala-CP](https://github.com/mcapuccini/scala-cp) by Marco Capuccini (2020) 🔥🔥🔥🔥🔥