Physics
- Toward an AI Physicist for Unsupervised Learning ⭐
- AI Feynman: a Physics-Inspired Method for Symbolic Regression ⭐
- Accelerated Nuclear Magnetic Resonance Spectroscopy with Deep Learning
- Theory-guided Data Science: A New Paradigm for Scientific Discovery from Data
- Predicting Research Trends with Semantic and Neural Networks with an application in Quantum Physics
- Variational Autoencoders for New Physics Mining at the Large Hadron Collider
- Covariance in Physics and Convolutional Neural Networks
- Fast Solar Image Classification Using Deep Learning and its Importance for Automation in Solar Physics
- Physics-as-Inverse-Graphics: Joint Unsupervised Learning of Objects and Physics from Video
- Machine Learning in High Energy Physics Community White Paper ⭐
- TensorNetwork: A Library for Physics and Machine Learning
- Class Imbalance Techniques for High Energy Physics
- Wave Physics as an Analog Recurrent Neural Network
- Like Quantum Computing without Quantum Physics: Is it How the Brain Works?
- Heavy Rain Image Restoration: Integrating Physics Model and Conditional Adversarial Learning
- Including Physics in Deep Learning -- An example from 4D seismic pressure saturation inversion
- TossingBot: Learning to Throw Arbitrary Objects with Residual Physics
- Machine Learning Solutions for High Energy Physics: Applications to Electromagnetic Shower Generation, Flavor Tagging, and the Search for di-Higgs Production ⭐
- The Calabi-Yau Landscape: from Geometry, to Physics, to Machine-Learning
- Proceedings of the 2018 Workshop on Compositional Approaches in Physics, NLP, and Social Sciences
- Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
- End-to-End Physics Event Classification with the CMS Open Data: Applying Image-based Deep Learning on Detector Data to Directly Classify Collision Events at the LHC
- Fast inference of deep neural networks in FPGAs for particle physics
- JUNIPR: a Framework for Unsupervised Machine Learning in Particle Physics
- Application of a Convolutional Neural Network for image classification to the analysis of collisions in High Energy Physics
- Deep Extreme Feature Extraction: New MVA Method for Searching Particles in High Energy Physics
- Using Machine Learning to Predict the Evolution of Physics Research
- Machine Learning Approach to Earthquake Rupture Dynamics
- Machine learning for long-distance quantum communication
- Quantum-assisted associative adversarial network: Applying quantum annealing in deep learning
- Like Quantum Computing without Quantum Physics: Is it How the Brain Works?
- Efficient Learning for Deep Quantum Neural Networks
- Quantum Memristors in Quantum Photonics
- The Ramanujan Machine: Automatically Generated Conjectures on Fundamental Constants
- Explainable Machine Learning for Scientific Insights and Discoveries
- A Differentiable Programming System to Bridge Machine Learning and Scientific Computing
- MadMiner: Machine learning-based inference for particle physics
- Discovery of Physics from Data: Universal Laws and Discrepancy Models ⭐
- How the fundamental concepts of mathematics and physics explain deep learning
- Ultimate Intelligence Part II: Physical Measure and Complexity of Intelligence
Chemistry
- A survey on Big Data and Machine Learning for Chemistry
- Deep Learning for Computational Chemistry
- Neural networks for the prediction organic chemistry reactions
- Using Attribution to Decode Dataset Bias in Neural Network Models for Chemistry
- Molecular Transformer - A Model for Uncertainty-Calibrated Chemical Reaction Prediction
- DeepFreak: Learning Crystallography Diffraction Patterns with Automated Machine Learning
- Interpretable Deep Learning in Drug Discovery
- Optimization of Molecules via Deep Reinforcement Learning
- Atomistic structure learning
- Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation
- Generating equilibrium molecules with deep neural networks
- ANI-1: A data set of 20M off-equilibrium DFT calculations for organic molecules
- Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models
- Molecular Property Prediction: A Multilevel Quantum Interactions Modeling Perspective
- Unifying machine learning and quantum chemistry -- a deep neural network for molecular wavefunctions
- Parameterized quantum circuits as machine learning models
- Generative Models for Automatic Chemical Design
- Graph Informer Networks for Molecules
Astronomy
- Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy
- ASTROMLSKIT: A New Statistical Machine Learning Toolkit: A Platform for Data Analytics in Astronomy
- Deep Learning for Energy Estimation and Particle Identification in Gamma-ray Astronomy
- Particle identification in ground-based gamma-ray astronomy using convolutional neural networks
- Machine Learning in Astronomy: A Case Study in Quasar-Star Classification
- Distributed image reconstruction for very large arrays in radio astronomy
- SKYNET: an efficient and robust neural network training tool for machine learning in astronomy
- Convolutional neural networks: a magic bullet for gravitational-wave detection?
- Desaturating EUV observations of solar flaring storms
- Evolutionary Deep Learning to Identify Galaxies in the Zone of Avoidance
- Forging new worlds: high-resolution synthetic galaxies with chained generative adversarial networks
- NEARBY Platform for Automatic Asteroids Detection and EURONEAR Surveys
- Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era ⭐
- Advanced Image Processing for Astronomical Images
- Computational Intelligence Challenges and Applications on Large-Scale Astronomical Time Series Databases
- Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding
- Moon Search Algorithms for NASA's Dawn Mission to Asteroid Vesta
- A Novel Deep Neural Network Architecture for Mars Visual Navigation
- SPASS: Scientific Prominence Active Search System with Deep Image Captioning Network
- FPGA Architecture for Deep Learning and its application to Planetary Robotics
- Solar-Sail Trajectory Design for Multiple Near Earth Asteroid Exploration Based on Deep Neural Networks
- Automated Prototype for Asteroids Detection
- Seeker based Adaptive Guidance via Reinforcement Meta-Learning Applied to Asteroid Close Proximity Operations
- CosmoFlow: Using Deep Learning to Learn the Universe at Scale
- From Dark Matter to Galaxies with Convolutional Networks
- Single-epoch supernova classification with deep convolutional neural networks
- Estimating Cosmological Parameters from the Dark Matter Distribution
- Enabling Dark Energy Science with Deep Generative Models of Galaxy Images
- Machine Learning for Searching the Dark Energy Survey for Trans-Neptunian Objects
Geography/Climate Change
- Urban morphology meets deep learning: Exploring urban forms in one million cities, town and villages across the planet
- PlaNet - Photo Geolocation with Convolutional Neural Networks
- Exploring Urban Air Quality with MAPS: Mobile Air Pollution Sensing
- AI-based evaluation of the SDGs: The case of crop detection with earth observation data
- Enabling FAIR Research in Earth Science through Research Objects ⭐
- Automatic Spatial Context-Sensitive Cloud/Cloud-Shadow Detection in Multi-Source Multi-Spectral Earth Observation Images: AutoCloud+
- DeepGlobe 2018: A Challenge to Parse the Earth through Satellite Images
- Satellite-Net: Automatic Extraction of Land Cover Indicators from Satellite Imagery by Deep Learning
- SpaceNet: A Remote Sensing Dataset and Challenge Series
- SOMOSPIE: A modular SOil MOisture SPatial Inference Engine based on data driven decisions
- DOTA: A Large-scale Dataset for Object Detection in Aerial Images
- On-Orbit Smart Camera System to Observe Illuminated and Unilluminated Space Objects
- Learning Spectral-Spatial-Temporal Features via a Recurrent Convolutional Neural Network for Change Detection in Multispectral Imagery
- Using Satellite Imagery for Good: Detecting Communities in Desert and Mapping Vaccination Activities
- Merging Satellite Measurements of Rainfall Using Multi-scale Imagery Technique
- VARENN: Graphical representation of spatiotemporal data and application to climate studies
- Achieving Conservation of Energy in Neural Network Emulators for Climate Modeling
- Tackling Climate Change with Machine Learning ⭐
- Learning Radiative Transfer Models for Climate Change Applications in Imaging Spectroscopy
- ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events
- Application of Deep Convolutional Neural Networks for Detecting Extreme Weather in Climate Datasets
- Predicting Climate Variability over the Indian Region Using Data Mining Strategies
- Neural-networks for geophysicists and their application to seismic data interpretation
- Towards a method to anticipate dark matter signals with deep learning at the LHC
- Constraining dark matter annihilation with cosmic ray antiprotons using neural networks
Space