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Andrew Gordon Wilson

  1. Chronos: Learning the Language of Time Series
    2024/03/12 by Abdul Fatir Ansari, Ansari, Abdul Fatir, Lorenzo Stella +36 · 4 voices · 160 citations
    Computer Science · Physics and Astronomy · #Time Series Analysis and Forecasting #Advanced Text Analysis Techniques #Historical Astronomy and Related Studies
  2. Deep Learning is Not So Mysterious or Different
    2025/03/03 by Andrew Gordon Wilson, Wilson, Andrew Gordon · 31 voices · 26 citations
    Computer Science · #Explainable Artificial Intelligence (XAI) #Generative Adversarial Networks and Image Synthesis #Stochastic Gradient Optimization Techniques #cs.LG #stat.ML
  3. A Cookbook of Self-Supervised Learning
    2023/04/24 by Randall Balestriero, Balestriero, Randall, Mark Ibrahim +36 · 2 voices · 33 citations
    Computer Science · #Machine Learning and Data Classification
  4. Large Language Models Are Zero-Shot Time Series Forecasters
    2023/10/11 by Nate Gruver, Marc Finzi, Gruver, Nate +5 · 3 voices · 87 citations
    Computer Science · #Topic Modeling #Natural Language Processing Techniques #Advanced Text Analysis Techniques
  5. From Entropy to Epiplexity: Rethinking Information for Computationally Bounded Intelligence
    2026/01/06 by Marc Finzi, Shikai Qiu, Yiding Jiang +3 · 13 voices · 9 citations
    #cs.LG #stat.ML
  6. Averaging Weights Leads to Wider Optima and Better Generalization
    2018/03/14 by Pavel Izmailov, Izmailov, Pavel, D. A. Podoprikhin +7 · 121 citations
    Computer Science · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  7. GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration
    2018/09/28 by Jacob R. Gardner, Geoff Pleiss, Gardner, Jacob R. +7 · 95 citations
    Computer Science · Engineering · #Gaussian Processes and Bayesian Inference #Control Systems and Identification #Neural Networks and Applications
  8. Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs
    2018/02/27 by Timur Garipov, Pavel Izmailov, Garipov, Timur +7 · 66 citations
    Computer Science · #Advanced Neural Network Applications #Domain Adaptation and Few-Shot Learning #Adversarial Robustness in Machine Learning
  9. Deep Kernel Learning
    2015/11/06 by Andrew Gordon Wilson, Zhiting Hu, Wilson, Andrew Gordon +5 · 50 citations
    Computer Science · #Gaussian Processes and Bayesian Inference #Generative Adversarial Networks and Image Synthesis #Human Pose and Action Recognition
  10. A Simple Baseline for Bayesian Uncertainty in Deep Learning
    2019/02/07 by Wesley J. Maddox, Timur Garipov, Maddox, Wesley +7 · 71 citations
    Computer Science · #Gaussian Processes and Bayesian Inference #Adversarial Robustness in Machine Learning #Domain Adaptation and Few-Shot Learning
  11. The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning
    2023/04/11 by Micah Goldblum, Goldblum, Micah, Marc Finzi +5 · 2 voices · 9 citations
    Computer Science · #Computability, Logic, AI Algorithms #Machine Learning and Algorithms #Machine Learning and Data Classification #cs.LG #stat.ML
  12. Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations
    2022/04/06 by Polina Kirichenko, Kirichenko, Polina, Pavel Izmailov +3 · 36 citations
    Computer Science · #AI in cancer detection #Generative Adversarial Networks and Image Synthesis #Machine Learning and Data Classification
  13. Kernel Interpolation for Scalable Structured Gaussian Processes\n (KISS-GP)
    2015/03/03 by Andrew Gordon Wilson, Hannes Nickisch, Wilson, Andrew Gordon +1 · 21 citations
    Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Human Pose and Action Recognition #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Scientific Research and Discoveries
  14. What Are Bayesian Neural Network Posteriors Really Like?
    2021/04/29 by Pavel Izmailov, Sharad Vikram, Izmailov, Pavel +5 · 21 citations
    Computer Science · Mathematics · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods
  15. Generalizing Convolutional Neural Networks for Equivariance to Lie\n Groups on Arbitrary Continuous Data
    2020/02/25 by Marc Finzi, Samuel Stanton, Finzi, Marc +6 · 24 citations
    Computer Science · Biochemistry, Genetics and Molecular Biology · Materials Science · #Computational Physics and Python Applications #Protein Structure and Dynamics #Machine Learning in Materials Science
  16. Why Normalizing Flows Fail to Detect Out-of-Distribution Data
    2020/06/15 by Polina Kirichenko, Kirichenko, Polina, Pavel Izmailov +3 · 19 citations
    Computer Science · #Anomaly Detection Techniques and Applications #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  17. On Feature Learning in the Presence of Spurious Correlations
    2022/10/20 by Pavel Izmailov, Polina Kirichenko, Izmailov, Pavel +5 · 21 citations
    Engineering · Computer Science · #Industrial Vision Systems and Defect Detection #Face and Expression Recognition #Image Enhancement Techniques
  18. Does Knowledge Distillation Really Work?
    2021/06/10 by Samuel Stanton, Pavel Izmailov, Stanton, Samuel +7 · 18 citations
    Computer Science · Physics and Astronomy · #Domain Adaptation and Few-Shot Learning #Adversarial Robustness in Machine Learning #Model Reduction and Neural Networks
  19. Gaussian Process Regression Networks
    2011/10/19 by Andrew Gordon Wilson, Wilson, Andrew Gordon, David A. Knowles +3 · 13 citations
    Computer Science · Engineering · #Gaussian Processes and Bayesian Inference #Control Systems and Identification #Fault Detection and Control Systems
  20. Stochastic Variational Deep Kernel Learning
    2016/11/01 by Andrew Gordon Wilson, Wilson, Andrew Gordon, Zhiting Hu +5 · 11 citations
    Computer Science · Environmental Science · #Air Quality Monitoring and Forecasting #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME)
  21. Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
    2019/02/11 by Ruqi Zhang, Zhang, Ruqi, Chunyuan Li +7 · 11 citations
    Computer Science · Mathematics · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Markov Chains and Monte Carlo Methods #Methodology (stat.ME)
  22. Residual Pathway Priors for Soft Equivariance Constraints
    2021/12/02 by Marc Finzi, Gregory W. Benton, Finzi, Marc +3 · 9 citations
    Computer Science · Engineering · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics #Robot Manipulation and Learning
  23. Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI
    2024/02/01 by Theodore Papamarkou, Papamarkou, Theodore, Maria Skoularidou +47 · 1 voice · 12 citations
    #cs.LG #stat.ML
  24. Non-Vacuous Generalization Bounds for Large Language Models
    2023/12/28 by Sanae Lotfi, Marc Finzi, Lotfi, Sanae +9 · 2 voices · 8 citations
    Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Natural Language Processing Techniques #Speech Recognition and Synthesis #Topic Modeling
  25. Modeling Caption Diversity in Contrastive Vision-Language Pretraining
    2024/04/30 by Samuel Lavoie, Polina Kirichenko, Lavoie, Samuel +11 · 2 voices · 10 citations
    #cs.CV #cs.AI #cs.CL #cs.LG
  26. A Study of Bayesian Neural Network Surrogates for Bayesian Optimization
    2023/05/31 by Yucen Lily Li, Tim G. J. Rudner, Li, Yucen Lily +3 · 10 citations
    Computer Science · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification
  27. Subspace Inference for Bayesian Deep Learning
    2019/07/17 by Pavel Izmailov, Wesley J. Maddox, Izmailov, Pavel +9 · 7 citations
    Computer Science · #Gaussian Processes and Bayesian Inference #Anomaly Detection Techniques and Applications #Generative Adversarial Networks and Image Synthesis
  28. PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization
    2022/11/24 by Sanae Lotfi, Lotfi, Sanae, Marc Finzi +9 · 9 citations
    Computer Science · Physics and Astronomy · #Advanced Neural Network Applications #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks
  29. Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints
    2020/10/26 by Marc Finzi, Finzi, Marc, Ke Alexander Wang +3 · 6 citations
    Computer Science · Engineering · Physics and Astronomy · #Computational Physics (physics.comp-ph) #Computational Physics and Python Applications #Control and Stability of Dynamical Systems #Data Analysis #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Modeling and Simulation Systems #Neural Networks and Applications #Statistics and Probability (physics.data-an) #Time Series Analysis and Forecasting
  30. Exact Gaussian Processes on a Million Data Points
    2019/03/19 by Ke Alexander Wang, Wang, Ke Alexander, Geoff Pleiss +9 · 5 citations
    Computer Science · Engineering · #Control Systems and Identification #Distributed #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Parallel #and Cluster Computing (cs.DC)
  31. Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks
    2025/07/02 by Shikai Qiu, Qiu, Shikai, Lechao Xiao +7 · 3 voices · 11 citations
    #cs.LG
  32. Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks
    2023/10/30 by Micah Goldblum, Goldblum, Micah, Hossein Souri +23 · 8 citations
    Computer Science · #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multimodal Machine Learning Applications
  33. The Lie Derivative for Measuring Learned Equivariance
    2022/10/06 by Nate Gruver, Marc Finzi, Gruver, Nate +5 · 6 citations
    Computer Science · Materials Science · Physics and Astronomy · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Materials Science #Model Reduction and Neural Networks #Neural Networks and Applications
  34. Thoughts on Massively Scalable Gaussian Processes
    2015/11/05 by Andrew Gordon Wilson, Wilson, Andrew Gordon, Christoph Dann +3 · 3 citations
    Computer Science · Physics and Astronomy · #Advanced Multi-Objective Optimization Algorithms #Advanced Thermodynamics and Statistical Mechanics #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME)
  35. Small Batch Size Training for Language Models: When Vanilla SGD Works, and Why Gradient Accumulation Is Wasteful
    2025/07/09 by Martin Marek, Sanae Lotfi, Marek, Martin +7 · 4 voices · 12 citations
    Computer Science · Medicine · #Topic Modeling #Natural Language Processing Techniques #Artificial Intelligence in Healthcare and Education
  36. Visual Explanations of Image-Text Representations via Multi-Modal Information Bottleneck Attribution
    2023/12/28 by Ying Wang, Tim G. J. Rudner, Wang, Ying +3 · 6 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multimodal Machine Learning Applications #Topic Modeling
  37. Student-t Processes as Alternatives to Gaussian Processes
    2014/02/18 by Amar Shah, Andrew Gordon Wilson, Shah, Amar +3 · 3 citations
    Computer Science · Decision Sciences · #Gaussian Processes and Bayesian Inference #Advanced Multi-Objective Optimization Algorithms #Optimal Experimental Design Methods
  38. Rethinking Parameter Counting in Deep Models: Effective Dimensionality Revisited
    2020/03/04 by Wesley J. Maddox, Gregory W. Benton, Maddox, Wesley J. +3 · 4 citations
    Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks
  39. On the model-based stochastic value gradient for continuous reinforcement learning
    2020/08/28 by Brandon Amos, Samuel Stanton, Amos, Brandon +5 · 3 citations
    Biochemistry, Genetics and Molecular Biology · Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Gene Regulatory Network Analysis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics #Robotics (cs.RO)
  40. Compute Better Spent: Replacing Dense Layers with Structured Matrices
    2024/06/10 by Shikai Qiu, Andres Potapczynski, Qiu, Shikai +7 · 1 voice · 4 citations
    #cs.LG
  41. How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization
    2022/10/12 by Jonas Geiping, Geiping, Jonas, Micah Goldblum +9 · 3 citations
    Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning and Algorithms #Machine Learning and Data Classification
  42. What do Vision Transformers Learn? A Visual Exploration
    2022/12/13 by Amin Ghiasi, Ghiasi, Amin, Hamid Kazemi +13 · 3 citations
    Computer Science · #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Multimodal Machine Learning Applications #Visual Attention and Saliency Detection
  43. Learning Invariances in Neural Networks
    2020/10/22 by Gregory W. Benton, Marc Finzi, Benton, Gregory +5 · 2 citations
    Computer Science · Materials Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Materials Science #Neural Networks and Applications
  44. Probabilistic FastText for Multi-Sense Word Embeddings
    2018/06/07 by Ben Athiwaratkun, Athiwaratkun, Ben, Andrew Gordon Wilson +3 · 2 citations
    Computer Science · #Topic Modeling #Natural Language Processing Techniques #Text Readability and Simplification
  45. Conditioning Sparse Variational Gaussian Processes for Online Decision-making
    2021/10/28 by Wesley J. Maddox, Samuel C. Stanton, Maddox, Wesley J. +4 · 2 citations
    Computer Science · #Advanced Multi-Objective Optimization Algorithms #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
  46. Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors
    2022/05/20 by Ravid Shwartz-Ziv, Micah Goldblum, Shwartz-Ziv, Ravid +11 · 2 citations
    Computer Science · #Domain Adaptation and Few-Shot Learning #Gaussian Processes and Bayesian Inference #Adversarial Robustness in Machine Learning
  47. Chroma-VAE: Mitigating Shortcut Learning with Generative Classifiers
    2022/11/28 by Wanqian Yang, Polina Kirichenko, Yang, Wanqian +5 · 2 citations
    Computer Science · #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Music and Audio Processing #Topic Modeling
  48. A Stable and Scalable Method for Solving Initial Value PDEs with Neural Networks
    2023/04/28 by Marc Finzi, Finzi, Marc, Andres Potapczynski +5 · 2 citations
    Engineering · Mathematics · Physics and Astronomy · #Energy Load and Power Forecasting #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Numerical Analysis (math.NA) #Numerical methods for differential equations
  49. Out-of-Distribution Detection Methods Answer the Wrong Questions
    2025/07/02 by Yucen Lily Li, Li, Yucen Lily, Dan Lu +11 · 7 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Data Stream Mining Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  50. GPatt: Fast Multidimensional Pattern Extrapolation with Gaussian Processes
    2013/10/20 by Andrew Gordon Wilson, Wilson, Andrew Gordon, Elad Gilboa +5 · 1 citation
    Computer Science · Engineering · #Artificial Intelligence (cs.AI) #Control Systems and Identification #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Time Series Analysis and Forecasting
  51. Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences
    2024/12/10 by Alan Nawzad Amin, Nate Gruver, Amin, Alan Nawzad +15 · 2 voices · 3 citations
    #stat.ML #cs.LG #q-bio.BM
  52. Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models
    2024/07/25 by Sanae Lotfi, Yilun Kuang, Lotfi, Sanae +9 · 1 voice · 3 citations
    #stat.ML #cs.LG
  53. Kernel Interpolation for Scalable Online Gaussian Processes
    2021/03/02 by Samuel Stanton, Stanton, Samuel, Wesley J. Maddox +5 · 1 citation
    Computer Science · Engineering · Decision Sciences · #Gaussian Processes and Bayesian Inference #Control Systems and Identification #Advanced Bandit Algorithms Research
  54. Perspectives on the State and Future of Deep Learning - 2023
    2023/12/07 by Micah Goldblum, Anima Anandkumar, Goldblum, Micah +17 · 3 voices
    #cs.AI #cs.LG
  55. Task-agnostic Continual Learning with Hybrid Probabilistic Models
    2021/06/24 by Polina Kirichenko, Mehrdad Farajtabar, Kirichenko, Polina +15 · 1 citation
    Computer Science · #Adversarial Robustness in Machine Learning #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and ELM
  56. Simplifying Neural Network Training Under Class Imbalance
    2023/12/05 by Ravid Shwartz-Ziv, Micah Goldblum, Shwartz-Ziv, Ravid +7 · 1 voice · 1 citation
    Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #cs.AI #cs.LG
  57. Learning Multimodal Data Augmentation in Feature Space
    2022/12/29 by Zichang Liu, Zhiqiang Tang, Liu, Zichang +11 · 1 citation
    Computer Science · #Computation and Language (cs.CL) #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multimodal Machine Learning Applications #Natural Language Processing Techniques
  58. Understanding the Detrimental Class-level Effects of Data Augmentation
    2023/12/07 by Polina Kirichenko, Mark Ibrahim, Kirichenko, Polina +11 · 1 citation
    Computer Science · Medicine · #COVID-19 diagnosis using AI #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification
  59. Function-Space Regularization in Neural Networks: A Probabilistic Perspective
    2023/12/28 by Tim G. J. Rudner, Rudner, Tim G. J., Sanyam Kapoor +5 · 1 citation
    Computer Science · #Neural Networks and Applications #Advanced Neural Network Applications #Stochastic Gradient Optimization Techniques
  60. Requential Coding: Pushing the Limits of Model Compression with Self-Generated Training Data
    2026/07/13 by Shikai Qiu, Marc Finzi, Yujia Zheng +2 · 3 voices
    #cs.LG
  61. A Nearby Dark Molecular Cloud in the Local Bubble Revealed via H2 Fluorescence
    2025/04/24 by Blakesley Burkhart, Burkhart, Blakesley, T. E. Dharmawardena +43 · 2 citations
    Chemistry · Physics and Astronomy · #Astrophysics and Star Formation Studies #Astrophysics of Galaxies (astro-ph.GA) #FOS: Physical sciences #Fullerene Chemistry and Applications #Scientific Research and Discoveries