Stanton, Samuel

1. 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
2. Does Knowledge Distillation Really Work?
   2021/06/10 by Samuel Stanton, Stanton, Samuel, Pavel Izmailov +7 · 18 citations
   Computer Science · Physics and Astronomy · #Domain Adaptation and Few-Shot Learning #Adversarial Robustness in Machine Learning #Model Reduction and Neural Networks
3. Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders
   2022/03/23 by Stanton, Samuel, Maddox, Wesley, Gruver, Nate +4 · 14 citations
   #FOS: Biological sciences #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural and Evolutionary Computing (cs.NE) #Quantitative Methods (q-bio.QM)
4. GAUCHE: A Library for Gaussian Processes in Chemistry
   2022/12/06 by Griffiths, Ryan-Rhys, Klarner, Leo, Moss, Henry B. +24 · 6 citations
   #Chemical Physics (physics.chem-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Materials Science (cond-mat.mtrl-sci)
5. On the model-based stochastic value gradient for continuous reinforcement learning
   2020/08/28 by Brandon Amos, Amos, Brandon, Samuel Stanton +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)
6. Conformal Validity Guarantees Exist for Any Data Distribution (and How to Find Them)
   2024/05/10 by Drew Prinster, Samuel C. Stanton, Prinster, Drew +5 · 6 citations
   Decision Sciences · Mathematics · #Advanced Statistical Process Monitoring #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistical Methods and Inference
7. Concept Bottleneck Language Models For protein design
   2024/11/09 by Aya Abdelsalam Ismail, Ismail, Aya Abdelsalam, Tuomas Oikarinen +21 · 3 voices · 4 citations
   Biochemistry, Genetics and Molecular Biology · #Biomedical Text Mining and Ontologies #Machine Learning in Bioinformatics #Microbial Metabolic Engineering and Bioproduction #cs.LG
8. 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
9. Kernel Interpolation for Scalable Online Gaussian Processes
   2021/03/02 by Samuel Stanton, Wesley J. Maddox, Stanton, Samuel +5 · 1 citation
   Computer Science · Engineering · Decision Sciences · #Gaussian Processes and Bayesian Inference #Control Systems and Identification #Advanced Bandit Algorithms Research
10. Closed-Form Test Functions for Biophysical Sequence Optimization Algorithms
    2024/06/28 by Stanton, Samuel, Alberstein, Robert, Frey, Nathan +2 · 2 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Neural and Evolutionary Computing (cs.NE)
11. Deconstructing the Inductive Biases of Hamiltonian Neural Networks
    2022/02/10 by Gruver, Nate, Finzi, Marc, Stanton, Samuel +1 · 1 citation
    #Data Analysis #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics and Probability (physics.data-an)