some papers

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Author Title Year Topics
Weyn et al. Can Machines Learn to Predict Weather 2019 weather forecasting, deep learning
Raghu et al. Transfusion Understanding Transfer Learning for Medical Imaging 2019 deep learning properties, transfer learning
Caron et al. Finding winning tickets with limited (or no) supervision 2020 sparse neural networks, lottery ticket hypothesis
Liu et al. An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution 2018 deep learning properties
Gang et al. Hamiltonian Neural Networks 2019 dynamical systems, deep learning properties
Yoon et al. Time-series Generative Adversarial Networks 2019 time series, generative adversarial networks
Xu et al. GAN-based Virtual Re-Staining A Promising Solution for Whole Slide Image Analysis 2019 generative adversarial networks, computational pathology
Spector et al. Google’s Hybrid Approach to Research 2012 research engineering processes
Zhou et al. Deconstructing Lottery Tickets: Zeros, Signs and Supermasks 2019 sparse neural networks, lottery ticket hypothesis, deep learning properties
DJ Hand Classifier Technology and the Illusion of Progress 2006 statistical analysis, machine learning
Morcos et al. One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers 2019 sparse neural networks, lottery ticket hypothesis
Lee et al. Harmonizing Maximum Likelihood with GANs for Multimodal Conditional Generation 2019 generative adversarial networks, deep learning properties
Scher et al. Weather and climate forecasting with neural networks using general circulation models (GCMs) with different complexity as a study ground 2019 weather systems, deep learning
Yu et al. Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP 2020 sparse neural networks, lottery ticket hypothesis, reinforcement learning, natural language processing
Wang et al. SAR-to-Optical Image Translation Using Supervised Cycle-Consistent Adversarial Networks 2019 generative adversarial networks, remote sensing
Renda et al. Comparing fine-tuning and rewinding in neural network prunning 2020 sparse neural networks, lottery ticket hypothesis
Greydanus et al. Hamiltonian Neural Networks 2019 dynamical systems, deep learning properties
Franceschi et al. Unsupervised Scalable Representation Learning for Multivariate Time Series 2019 self-supervised learning, time series
Rasp et al. WeatherBench A benchmark dataset for data-driven weather forecasting 2019 weather systems, deep learning
Frankle et al. The Lottery Ticket Hypothesis Finding Sparse, Trainable Neural Networks 2019 sparse neural networks, lottery ticket hypothesis
Liu et al. A comparison of deep learning performance against health-care professionals in detecting deseases from medical imaging: a systematic review and meta-analysis 2019 deep learning, medical review
Kohl et al. A Probabilistic U-Net for Segmentation of Ambiguous Images 2018 probabilistic deep learning, computer vision, uncertainty quantification
Lee et al. Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples 2018 deep learning properties
Lucic et al. Are GANs Created Equal? A Large-Scale Study 2018 ablation study, deep learning properties, generative adversarial networks
Fruhwirt et al. Towards better healthcare What could and should be automated 2019 medical review
Huang et al. Diversity-Aware Vehicle Motion Prediction via Latent Semantic Sampling 2019 probabilistic deep learning, uncertainty quantification
Li et al. Measuring the Intrinsic Dimension of Objective Landscapes 2018 deep learning properties
Frankle et al. Linear Mode Connectivity and The Lottery Ticket Hypothesis 2019 sparse neural networks, lottery ticket hypothesis
Rivenson et al. Virtual histological staining of unlabelled tissue 2019 generative adversarial networks, computational pathology
Jiang et al. Fantastic generalisation measures and where to find them 2020 ablation study, deep learning properties, causal inference
Hagendorff The Ethics of AI Ethics 2018 AI ethics
Reyes et al. Sar-to-optical image translation based on conditional generative adversarial networks—Optimization, opportunities and limits 2019 generative adversarial networks, remote sensing
Kvamme et al. Continuous and Discrete-Time Survival Prediction with Neural Networks 2019 deep learning, survival analysis
Zhu et al. Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks 2018 generative adversarial networks, computer vision
Arbabi et al. Data-driven modeling of strongly nonlinear chaotic systems with non-Gaussian statistics 2019 dynamical systems, weather systems, stochastic modeling
Shafani et al. Adversarially Robust Transfer Learning 2020 adversarial learning, transfer learning, deep learning properties
Ben Haim et al. Inundation Modeling in Data Scarce Regions 2019 hydrology, remote sensing, deep learning
Dueben et al. Challenges and design choices for global weather and climate models based on machine learning 2020 weather systems
Hjelm et al. Learning deep representations by mutual information estimation and maximisation 2019 self-supervised learning, deep learning
Levy et al. Preliminary Evaluation of the Utility of Deep Generative Histopathology Image Translation at a Mid-Sized NCI Cancer Center 2020 generative adversarial networks, computational pathology
Scher et al. Generalization properties of feed-forward neural networks trained on Lorenz systems 2019 dynamical systems, deep learning
Sculley et al. Hidden Technical Debt in Machine Learning Systems 2015 research engineering processes
Hwang et al. Improving Subseasonal Forecasting in the Western U.S. with Machine Learning 2019 weather systems, statistical machine learning
Wang et al. Picking winning tickets by preserving gradient flow 2020 sparse neural networks, lottery ticket hypothesis
Lee et al. Set Transformer A Framework for Attention-based Permutation-Invariant Neural Networks 2019 deep learning on sets, multiple instance learning
Le et al. Fastfood Approximating Kernel Expansion in Log Linear Time 2013 machine learning, kernel methods
Frankle et al. The Early Phase of Neural Networks Training 2020 deep learning ablation study, deep learning properties, sparse neural networks
Weyn et al. Improving data-driven global weather prediction using deep convolutional neural networks on a cubed sphere 2020 weather systems, deep learning
Schmidt et al. Distilling free-form natural laws from experimental data 2009 dynamical systems
Groenke et al. ClimAlign Unsupervised statistical downscaling of climate variables via normalizing flows 2020 normalizing flows, deep learning, climate modeling
Ruthanne Huising Can You Know Too Much About Your Ogranisation 2019 sociology, management
Grover et al AlignFlow Cycle Consistent Learning from Multiple Domains via Normalizing Flows 2020 normalizing flows
Rezendle et al. Variational Inference with Normalizing Flows 2015 normalizing flows
Desai et al VirTex Learning Visual Representations from Textual Annotations 2020 computer vision, image captioning, deep learning properties
Tschannen et al. On Mutual Information Maximization for Representation Learning 2020 self-supervised learning
Radford et al. Language Models are Unsupervised Multitask Learners 2019 deep learning, natural language processing
Radford et al. Improving Language Understanding by Generative Pre-Training 2018 deep learning, natural language processing
Venkatesh Rao A Big Little Idea Called Legibility 2010 sociology, antropology
Ding et al. Coherence-Aware Neural Topic Modeling 2018 natural language processing
David Graeber Bullshit jobs 2013 sociology
Chapwufa et al. Adversarial Time-to-Event Modeling 2018 survival analysis, generative adversarial networks
Merity S. Single Headed Attention RNN Stop Thinking With Your Head 2019 RNN, deep learning ablation study
Shi et al. Adapting Neural Networks for the Estimation of Treatment Effects 2019 deep learning, causal inference, potential outcomes
Rosenbaum et al. The central role of the propensity score in observational studies for causal effects 1983 potential outcomes, statistics
GomezUribe et al. The Netflix Recommender System Algorithms, Business Value, and Innovation 2015 recommender systems, causal inference, ml infrastructure
Avati et al. Countdown Regression Sharp and Calibrated Survival Predictions 2019 survival analysis
Louizos et al. Causal Effect Inference with Deep Latent-Variable Models 2017 causal inference, amortized variational inference
Bernardi et al. 150 successful Machine Learning models 6 lessons learned at Booking dot com 2019 ml infrastructure
Diamontopoulos et al. Engineering for a science-centric experimentation platform 2020 ml infrastructure
Vartak et al. A Meta-Learning Perspective on Cold-Start Recommendations for Items 2017 recommender systems, deep learning, meta learning
Chapwufa et al. Survival Analysis meets Counterfactual Inference 2020 causal inference, survival analysis, normalising flows
Shalit et al. Estimating individual treatment effect generalization bounds and algorithms 2017 deep learning, causal inference, potential outcomes
Schuler et al. Targeted Maximum Likelihood Estimation for Causal Inference in Observational Studies 2016 TMLE, potential outcomes, statistics
DAmour et al. Overlap in Observational Studies with High-Dimensional Covariates 2020 causal inference, statistics
Gutierrez et al. Causal Inference and Uplift Modelling A Review of the Literature 2017 uplift modeling, causal inference
Jaskowski et al. Uplift Modeling For Clinical Data 2012 uplift modeling
Hu et al. Estimating heterogeneous survival treatment effect in observational data using machine learning 2020 survival analysis, potential outcomes, ablation study
Murdoch et al. P-Values are Random Variables 2008 statistics
Kaplan et al. Scaling Laws for Neural Language Models 2020 deep learning, natural language processing
Resnick et al. Probing the State of the Art_ A Critical Look at Visual Representation Evaluation 2020 deep learning, representation learning
Ilse et al. Selecting Data Augmentation for Simulating Intervention 2020 causal inference, deep learning, data augmentation
Hoel The Overfitted Brain Dreams evolved to assist generalization 2020 neuro science
Whitney et al. Evaluating representations by the complexity of learning low-loss predictors 2020 deep learning properties
Ilse et al. Selecting Data Augmentation for Simulating Intervention 2020 deep learning, data augmentation, causal inference
Luo et al. Differentiable Learning-to-Normalize via Switchable Normalization 2019 deep learning properties, ablation study
Rosenberg et al. Astronomy in Everyday Life 2014 astronomy
Northcutt et al. Confident Learning Estimating Uncertainty in Dataset Labels 2020 label noise, uncertainty quantification
Sengupta et al. Ensembling geophysical models with Bayesian Neural Networks 2020 deep learning, uncertainty quantification, weather systems
Liu et al. SphereFace Deep Hypersphere Embedding for Face Recognition 2017 computer vision, facial recognition
Wang et al. Visual Commonsense R-CNN 2020 computer vision, deep learning, causal inference
Castro et al. Causality matters in medical imaging 2019 causal inference
Johansson et al. Learning Representations for Counterfactual Inference 2018 causal inference, deep learning
Shi et al. Adapting Neural Networks for the Estimation of Treatment Effects 2019 causal inference, deep learning
Bottou et al. Counterfactual Reasoning and Learning Systems The Example of Computational Advertising 2013 causal inference
Joon Oh et al. Modeling Uncertainty with Hedged Instance Embedding 2019 deep learning, uncertainty quantification
Schuler et al. Targeted Maximum Likelihood Estimation for Causal Inference in Observational Studies 2016 causal inference
Alaa et al. Validating Causal Inference Models via Influence Functions 2019 causal inference, model comparison
Jesson et al. Identifying Causal-Effect Inference Failure with Uncertainty-Aware Models 2020 uncertainty quantification, deep learning, causal inference
Gutierrez et al. Causal Inference and Uplift Modelling A Review of the Literature 2017 causal inference
HernandezGonzalez et al. Weak supervision and other non-standard classification problems a taxonomy 2016 weakly supervised learning, ablation study
Raf E. A Step Toward Quantifying Independently Reproducible Machine Learning Research 2019 statistical analysis, ablation study, machine learning
Lu et al. Deep Learning-based Computational Pathology Predicts Origins for Cancers of Unknown Primary 2020 deep learning, computational pathology
Cheng et al. Panoptic-DeepLab A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation 2020 deep learning, computer vision
Choi et al. StarGAN v2 Diverse Image Synthesis for Multiple Domains 2020 generative adversarial networks, computer vision
Sirinukunwattana et al. Image-based consensus molecular subtype (imCMS) classification of colorectal cancer using deep learning 2020 deep learning, computational pathology
Christidis et al. The increasing likelihood of temperature above 30 to 40 in the United Kingdom 2020 weather systems, climate modeling, statistical analysis
Armstrong et al. Exoplanet Validation with Machine Learning 50 new exoplanets 2020 astronomy, machine learning
Brown et al. Language Models are Few-Shot Learners 2020 deep learning, natural language processing
Chen et al. A general statistical framework for subgroup identification and comparative treatment scoring 2017 causal inference, potential outcomes, statistics
Wojtas et al. Feature Importance Ranking for Deep Learning 2020 feature selection, deep learning
Lewis et al. VOGUE Try On by StyleGAN Interpolation Optimization 2020 generative adversarial networks
Goldstein et al. XCAL Explicit Calibration for Survival Analysis 2020 survival analysis, uncertainty quantification