Andrew Gordon Wilson
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
71
Venues
7
Active years
2011–2025
Best venue rank
A*
Where they publish
Papers
71 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | AISTATS | Fine-Tuning with Uncertainty-Aware Priors Makes Vision and Language Foundation Models More Reliable. | Tim G. J. Rudner, Xiang Pan, Yucen Lily Li, Ravid Shwartz-Ziv, Andrew Gordon Wilson |
| 2025 | ICLR | Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences. | Alan Nawzad Amin, Nate Gruver, Yilun Kuang, Yucen Lily Li, Hunter Elliott, Calvin McCarter, Aniruddh Raghu, Peyton Greenside, Andrew Gordon Wilson |
| 2025 | ICLR | Compute-Optimal LLMs Provably Generalize Better with Scale. | Marc Anton Finzi, Sanyam Kapoor, Diego Granziol, Anming Gu, Christopher De Sa, J. Zico Kolter, Andrew Gordon Wilson |
| 2025 | ICML | Training Flexible Models of Genetic Variant Effects from Functional Annotations using Accelerated Linear Algebra. | Alan Nawzad Amin, Andres Potapczynski, Andrew Gordon Wilson |
| 2025 | ICML | Customizing the Inductive Biases of Softmax Attention using Structured Matrices. | Yilun Kuang, Noah Amsel, Sanae Lotfi, Shikai Qiu, Andres Potapczynski, Andrew Gordon Wilson |
| 2025 | ICML | Position: Supervised Classifiers Answer the Wrong Questions for OOD Detection. | Yucen Lily Li, Daohan Lu, Polina Kirichenko, Shikai Qiu, Tim G. J. Rudner, C. Bayan Bruss, Andrew Gordon Wilson |
| 2025 | ICML | Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization. | Luca Masserano, Abdul Fatir Ansari, Boran Han, Xiyuan Zhang, Christos Faloutsos, Michael W. Mahoney, Andrew Gordon Wilson, Youngsuk Park, Syama Sundar Rangapuram, Danielle C. Maddix, Bernie Wang |
| 2025 | ICML | Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks. | Shikai Qiu, Lechao Xiao, Andrew Gordon Wilson, Jeffrey Pennington, Atish Agarwala |
| 2025 | ICML | Position: Deep Learning is Not So Mysterious or Different. | Andrew Gordon Wilson |
| 2024 | AISTATS | Mind the GAP: Improving Robustness to Subpopulation Shifts with Group-Aware Priors. | Tim G. J. Rudner, Ya Shi Zhang, Andrew Gordon Wilson, Julia Kempe |
| 2024 | ICLR | Fine-Tuned Language Models Generate Stable Inorganic Materials as Text. | Nate Gruver, Anuroop Sriram, Andrea Madotto, Andrew Gordon Wilson, C. Lawrence Zitnick, Zachary W. Ulissi |
| 2024 | ICLR | A Study of Bayesian Neural Network Surrogates for Bayesian Optimization. | Yucen Lily Li, Tim G. J. Rudner, Andrew Gordon Wilson |
| 2024 | ICML | Scalable and Flexible Causal Discovery with an Efficient Test for Adjacency. | Alan Nawzad Amin, Andrew Gordon Wilson |
| 2024 | ICML | Position: The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning. | Micah Goldblum, Marc Anton Finzi, Keefer Rowan, Andrew Gordon Wilson |
| 2024 | ICML | Modeling Caption Diversity in Contrastive Vision-Language Pretraining. | Samuel Lavoie, Polina Kirichenko, Mark Ibrahim, Mido Assran, Andrew Gordon Wilson, Aaron C. Courville, Nicolas Ballas |
| 2024 | ICML | Non-Vacuous Generalization Bounds for Large Language Models. | Sanae Lotfi, Marc Anton Finzi, Yilun Kuang, Tim G. J. Rudner, Micah Goldblum, Andrew Gordon Wilson |
| 2024 | ICML | Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI. | Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, Jos Miguel Hernndez-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rgamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang |
| 2024 | ICML | Controllable Prompt Tuning For Balancing Group Distributional Robustness. | Hoang Phan, Andrew Gordon Wilson, Qi Lei |
| 2024 | ICML | Transferring Knowledge From Large Foundation Models to Small Downstream Models. | Shikai Qiu, Boran Han, Danielle C. Maddix, Shuai Zhang, Bernie Wang, Andrew Gordon Wilson |
| 2024 | ICML | Compute Better Spent: Replacing Dense Layers with Structured Matrices. | Shikai Qiu, Andres Potapczynski, Marc Anton Finzi, Micah Goldblum, Andrew Gordon Wilson |
| 2023 | AISTATS | Bayesian Optimization with Conformal Prediction Sets. | Samuel Stanton, Wesley J. Maddox, Andrew Gordon Wilson |
| 2023 | EMNLP | Automated Few-Shot Classification with Instruction-Finetuned Language Models. | Rami Aly, Xingjian Shi, Kaixiang Lin, Aston Zhang, Andrew Gordon Wilson |
| 2023 | ICLR | A Stable and Scalable Method for Solving Initial Value PDEs with Neural Networks. | Marc Anton Finzi, Andres Potapczynski, Matthew Choptuik, Andrew Gordon Wilson |
| 2023 | ICLR | How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization. | Jonas Geiping, Micah Goldblum, Gowthami Somepalli, Ravid Shwartz-Ziv, Tom Goldstein, Andrew Gordon Wilson |
| 2023 | ICLR | The Lie Derivative for Measuring Learned Equivariance. | Nate Gruver, Marc Anton Finzi, Micah Goldblum, Andrew Gordon Wilson |
| 2023 | ICLR | Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations. | Polina Kirichenko, Pavel Izmailov, Andrew Gordon Wilson |
| 2023 | ICLR | Transfer Learning with Deep Tabular Models. | Roman Levin, Valeriia Cherepanova, Avi Schwarzschild, Arpit Bansal, C. Bayan Bruss, Tom Goldstein, Andrew Gordon Wilson, Micah Goldblum |
| 2023 | ICLR | Learning Multimodal Data Augmentation in Feature Space. | Zichang Liu, Zhiqiang Tang, Xingjian Shi, Aston Zhang, Mu Li, Anshumali Shrivastava, Andrew Gordon Wilson |
| 2023 | ICML | User-defined Event Sampling and Uncertainty Quantification in Diffusion Models for Physical Dynamical Systems. | Marc Anton Finzi, Anudhyan Boral, Andrew Gordon Wilson, Fei Sha, Leonardo Zepeda-Nez |
| 2023 | ICML | Simple and Fast Group Robustness by Automatic Feature Reweighting. | Shikai Qiu, Andres Potapczynski, Pavel Izmailov, Andrew Gordon Wilson |
| 2023 | ICML | Function-Space Regularization in Neural Networks: A Probabilistic Perspective. | Tim G. J. Rudner, Sanyam Kapoor, Shikai Qiu, Andrew Gordon Wilson |
| 2022 | ICLR | Deconstructing the Inductive Biases of Hamiltonian Neural Networks. | Nate Gruver, Marc Anton Finzi, Samuel Don Stanton, Andrew Gordon Wilson |
| 2022 | ICML | Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes. | Gregory W. Benton, Wesley J. Maddox, Andrew Gordon Wilson |
| 2022 | ICML | Bayesian Model Selection, the Marginal Likelihood, and Generalization. | Sanae Lotfi, Pavel Izmailov, Gregory W. Benton, Micah Goldblum, Andrew Gordon Wilson |
| 2022 | ICML | Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders. | Samuel Stanton, Wesley J. Maddox, Nate Gruver, Phillip M. Maffettone, Emily Delaney, Peyton Greenside, Andrew Gordon Wilson |
| 2022 | ICML | Low-Precision Stochastic Gradient Langevin Dynamics. | Ruqi Zhang, Andrew Gordon Wilson, Christopher De Sa |
| 2022 | UAI | Low-precision arithmetic for fast Gaussian processes. | Wesley J. Maddox, Andres Potapczynski, Andrew Gordon Wilson |
| 2021 | AISTATS | Fast Adaptation with Linearized Neural Networks. | Wesley J. Maddox, Shuai Tang, Pablo Garcia Moreno, Andrew Gordon Wilson, Andreas C. Damianou |
| 2021 | AISTATS | Kernel Interpolation for Scalable Online Gaussian Processes. | Samuel Stanton, Wesley J. Maddox, Ian A. Delbridge, Andrew Gordon Wilson |
| 2021 | ICML | Loss Surface Simplexes for Mode Connecting Volumes and Fast Ensembling. | Gregory W. Benton, Wesley J. Maddox, Sanae Lotfi, Andrew Gordon Wilson |
| 2021 | ICML | A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups. | Marc Finzi, Max Welling, Andrew Gordon Wilson |
| 2021 | ICML | What Are Bayesian Neural Network Posteriors Really Like? | Pavel Izmailov, Sharad Vikram, Matthew D. Hoffman, Andrew Gordon Wilson |
| 2021 | ICML | SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes. | Sanyam Kapoor, Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson |
| 2021 | ICML | Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition. | Shengyang Sun, Jiaxin Shi, Andrew Gordon Wilson, Roger B. Grosse |
| 2020 | ICLR | Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning. | Ruqi Zhang, Chunyuan Li, Jianyi Zhang, Changyou Chen, Andrew Gordon Wilson |
| 2020 | ICML | Randomly Projected Additive Gaussian Processes for Regression. | Ian A. Delbridge, David Bindel, Andrew Gordon Wilson |
| 2020 | ICML | Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data. | Marc Finzi, Samuel Stanton, Pavel Izmailov, Andrew Gordon Wilson |
| 2020 | ICML | Semi-Supervised Learning with Normalizing Flows. | Pavel Izmailov, Polina Kirichenko, Marc Finzi, Andrew Gordon Wilson |
| 2019 | ICLR | There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average. | Ben Athiwaratkun, Marc Finzi, Pavel Izmailov, Andrew Gordon Wilson |
| 2019 | ICML | Simple Black-box Adversarial Attacks. | Chuan Guo, Jacob R. Gardner, Yurong You, Andrew Gordon Wilson, Kilian Q. Weinberger |
| 2019 | ICML | SWALP : Stochastic Weight Averaging in Low Precision Training. | Guandao Yang, Tianyi Zhang, Polina Kirichenko, Junwen Bai, Andrew Gordon Wilson, Christopher De Sa |
| 2019 | UAI | Subspace Inference for Bayesian Deep Learning. | Pavel Izmailov, Wesley J. Maddox, Polina Kirichenko, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson |
| 2019 | UAI | Practical Multi-fidelity Bayesian Optimization for Hyperparameter Tuning. | Jian Wu, Saul Toscano-Palmerin, Peter I. Frazier, Andrew Gordon Wilson |
| 2018 | ACL | Probabilistic FastText for Multi-Sense Word Embeddings. | Ben Athiwaratkun, Andrew Gordon Wilson, Anima Anandkumar |
| 2018 | AISTATS | Product Kernel Interpolation for Scalable Gaussian Processes. | Jacob R. Gardner, Geoff Pleiss, Ruihan Wu, Kilian Q. Weinberger, Andrew Gordon Wilson |
| 2018 | AISTATS | Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data. | William Herlands, Edward McFowland, Andrew Gordon Wilson, Daniel B. Neill |
| 2018 | ICLR | Hierarchical Density Order Embeddings. | Ben Athiwaratkun, Andrew Gordon Wilson |
| 2018 | ICML | Constant-Time Predictive Distributions for Gaussian Processes. | Geoff Pleiss, Jacob R. Gardner, Kilian Q. Weinberger, Andrew Gordon Wilson |
| 2018 | KDD | Automated Local Regression Discontinuity Design Discovery. | William Herlands, Edward McFowland III, Andrew Gordon Wilson, Daniel B. Neill |
| 2018 | UAI | Averaging Weights Leads to Wider Optima and Better Generalization. | Pavel Izmailov, Dmitrii Podoprikhin, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson |
| 2017 | ACL | Multimodal Word Distributions. | Ben Athiwaratkun, Andrew Gordon Wilson |
| 2016 | AISTATS | Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces. | William Herlands, Andrew Gordon Wilson, Hannes Nickisch, Seth R. Flaxman, Daniel B. Neill, Wilbert Van Panhuis, Eric P. Xing |
| 2016 | AISTATS | Bayesian Nonparametric Kernel-Learning. | Junier B. Oliva, Avinava Dubey, Andrew Gordon Wilson, Barnabs Pczos, Jeff G. Schneider, Eric P. Xing |
| 2016 | AISTATS | Deep Kernel Learning. | Andrew Gordon Wilson, Zhiting Hu, Ruslan Salakhutdinov, Eric P. Xing |
| 2015 | AISTATS | A la Carte - Learning Fast Kernels. | Zichao Yang, Andrew Gordon Wilson, Alexander J. Smola, Le Song |
| 2015 | ICML | Fast Kronecker Inference in Gaussian Processes with non-Gaussian Likelihoods. | Seth R. Flaxman, Andrew Gordon Wilson, Daniel B. Neill, Hannes Nickisch, Alexander J. Smola |
| 2015 | ICML | Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP). | Andrew Gordon Wilson, Hannes Nickisch |
| 2014 | AISTATS | Student-t Processes as Alternatives to Gaussian Processes. | Amar Shah, Andrew Gordon Wilson, Zoubin Ghahramani |
| 2013 | ICML | Gaussian Process Kernels for Pattern Discovery and Extrapolation. | Andrew Gordon Wilson, Ryan Prescott Adams |
| 2012 | ICML | Gaussian Process Regression Networks. | Andrew Gordon Wilson, David A. Knowles, Zoubin Ghahramani |
| 2011 | UAI | Generalised Wishart Processes. | Andrew Gordon Wilson, Zoubin Ghahramani |