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Samuel Stanton
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2020 – today
- 2024
- [c11]Drew Prinster, Samuel Don Stanton, Anqi Liu, Suchi Saria:
Conformal Validity Guarantees Exist for Any Data Distribution (and How to Find Them). ICML 2024 - [i13]Drew Prinster, Samuel Stanton, Anqi Liu, Suchi Saria:
Conformal Validity Guarantees Exist for Any Data Distribution (and How to Find Them). CoRR abs/2405.06627 (2024) - [i12]Samuel Stanton, Robert G. Alberstein, Nathan C. Frey, Andrew M. Watkins, Kyunghyun Cho:
Closed-Form Test Functions for Biophysical Sequence Optimization Algorithms. CoRR abs/2407.00236 (2024) - [i11]Angelica Chen, Samuel Don Stanton, Robert G. Alberstein, Andrew M. Watkins, Richard Bonneau, Vladimir Gligorijevic, Kyunghyun Cho, Nathan C. Frey:
LLMs are Highly-Constrained Biophysical Sequence Optimizers. CoRR abs/2410.22296 (2024) - 2023
- [c10]Samuel Stanton, Wesley J. Maddox, Andrew Gordon Wilson:
Bayesian Optimization with Conformal Prediction Sets. AISTATS 2023: 959-986 - [c9]Ryan-Rhys Griffiths, Leo Klarner, Henry B. Moss, Aditya Ravuri, Sang Truong, Yuanqi Du, Samuel Stanton, Gary Tom, Bojana Rankovic, Arian Rokkum Jamasb, Aryan Deshwal, Julius Schwartz, Austin Tripp, Gregory Kell, Simon Frieder, Anthony Bourached, Alex Chan, Jacob Moss, Chengzhi Guo, Johannes Peter Dürholt, Saudamini Chaurasia, Ji Won Park, Felix Strieth-Kalthoff, Alpha A. Lee, Bingqing Cheng, Alán Aspuru-Guzik, Philippe Schwaller, Jian Tang:
GAUCHE: A Library for Gaussian Processes in Chemistry. NeurIPS 2023 - [c8]Nate Gruver, Samuel Stanton, Nathan C. Frey, Tim G. J. Rudner, Isidro Hötzel, Julien Lafrance-Vanasse, Arvind Rajpal, Kyunghyun Cho, Andrew Gordon Wilson:
Protein Design with Guided Discrete Diffusion. NeurIPS 2023 - [i10]Nate Gruver, Samuel Stanton, Nathan C. Frey, Tim G. J. Rudner, Isidro Hötzel, Julien Lafrance-Vanasse, Arvind Rajpal, Kyunghyun Cho, Andrew Gordon Wilson:
Protein Design with Guided Discrete Diffusion. CoRR abs/2305.20009 (2023) - 2022
- [c7]Nate Gruver, Marc Anton Finzi, Samuel Don Stanton, Andrew Gordon Wilson:
Deconstructing the Inductive Biases of Hamiltonian Neural Networks. ICLR 2022 - [c6]Samuel Stanton, Wesley J. Maddox, Nate Gruver, Phillip M. Maffettone
, Emily Delaney, Peyton Greenside, Andrew Gordon Wilson:
Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders. ICML 2022: 20459-20478 - [i9]Nate Gruver, Marc Finzi, Samuel Stanton, Andrew Gordon Wilson:
Deconstructing the Inductive Biases of Hamiltonian Neural Networks. CoRR abs/2202.04836 (2022) - [i8]Samuel Stanton, Wesley J. Maddox, Nate Gruver, Phillip M. Maffettone, Emily Delaney, Peyton Greenside, Andrew Gordon Wilson:
Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders. CoRR abs/2203.12742 (2022) - [i7]Ji Won Park, Samuel Stanton, Saeed Saremi, Andrew M. Watkins, Henri Dwyer, Vladimir Gligorijevic, Richard Bonneau, Stephen Ra, Kyunghyun Cho:
PropertyDAG: Multi-objective Bayesian optimization of partially ordered, mixed-variable properties for biological sequence design. CoRR abs/2210.04096 (2022) - [i6]Samuel Stanton, Wesley J. Maddox, Andrew Gordon Wilson:
Bayesian Optimization with Conformal Coverage Guarantees. CoRR abs/2210.12496 (2022) - 2021
- [c5]Samuel Stanton, Wesley J. Maddox, Ian A. Delbridge, Andrew Gordon Wilson:
Kernel Interpolation for Scalable Online Gaussian Processes. AISTATS 2021: 3133-3141 - [c4]Brandon Amos, Samuel Stanton, Denis Yarats, Andrew Gordon Wilson:
On the model-based stochastic value gradient for continuous reinforcement learning. L4DC 2021: 6-20 - [c3]Wesley J. Maddox, Samuel Stanton, Andrew Gordon Wilson:
Conditioning Sparse Variational Gaussian Processes for Online Decision-making. NeurIPS 2021: 6365-6379 - [c2]Samuel Stanton, Pavel Izmailov, Polina Kirichenko, Alexander A. Alemi, Andrew Gordon Wilson:
Does Knowledge Distillation Really Work? NeurIPS 2021: 6906-6919 - [i5]Samuel Stanton, Wesley J. Maddox, Ian A. Delbridge, Andrew Gordon Wilson:
Kernel Interpolation for Scalable Online Gaussian Processes. CoRR abs/2103.01454 (2021) - [i4]Samuel Stanton, Pavel Izmailov, Polina Kirichenko, Alexander A. Alemi, Andrew Gordon Wilson:
Does Knowledge Distillation Really Work? CoRR abs/2106.05945 (2021) - [i3]Wesley J. Maddox, Samuel Stanton, Andrew Gordon Wilson:
Conditioning Sparse Variational Gaussian Processes for Online Decision-making. CoRR abs/2110.15172 (2021) - 2020
- [c1]Marc Finzi, Samuel Stanton, Pavel Izmailov, Andrew Gordon Wilson:
Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data. ICML 2020: 3165-3176 - [i2]Marc Finzi, Samuel Stanton, Pavel Izmailov, Andrew Gordon Wilson:
Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data. CoRR abs/2002.12880 (2020) - [i1]Brandon Amos, Samuel Stanton, Denis Yarats, Andrew Gordon Wilson:
On the model-based stochastic value gradient for continuous reinforcement learning. CoRR abs/2008.12775 (2020)
Coauthor Index
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