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Brooks Paige

25 papers · 2013–2025 · 4 conferences · across top CS/AI conferences

Achievements

πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (15) πŸ—ΊοΈ Taxonomy Completionist (10) 🧭 Keyword Pioneer 🌈 Renaissance Researcher (5) 🌍 Conference Polyglot (4) πŸƒ Academic Marathon (12) πŸ—ƒοΈ Keyword Collector (106) πŸ’Ž Century Club (25) πŸ”₯ Unstoppable (10) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer

Conferences

NIPS (10) ICML (7) AISTATS (5) ICLR (3)

Top co-authors

JosΓ© Miguel HernΓ‘ndez-Lobato (6) Frank Wood (6) John Bradshaw (3) Philip Torr (3) Siddharth N (3) Marwin Segler (2) Arnaud Doucet (2) Matt J. Kusner (2) David Barber (2) Mingtian Zhang (2)

Keywords

variational autoencoder (4) sequential monte carlo (4) generative model (3) variational inference (2) deep generative model (2) program synthesis (2) graphical model (2) markov chain monte carlo (2) probabilistic programming (2) molecule generation (2) disentangled representation (2) online learning (1) multi-modal learning (1) model interpretability (1) probabilistic inference (1) variable selection (1) representation learning (1) bayesian inference (1) mutual information (1) independent component analysis (1)

Papers

Right Now, Wrong Then: Non-Stationary Direct Preference Optimization under Preference Drift ICML 2025
Analysing the Generalisation and Reliability of Steering Vectors NIPS 2024
Gaussian Processes on Cellular Complexes ICML 2024
Diffusive Gibbs Sampling ICML 2024
AsEP: Benchmarking Deep Learning Methods for Antibody-specific Epitope Prediction NIPS 2024
Moment Matching Denoising Gibbs Sampling NIPS 2023
Fast and Scalable Spike and Slab Variable Selection in High-Dimensional Gaussian Processes AISTATS 2022
Learning Bijective Feature Maps for Linear ICA AISTATS 2021
Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models ICLR 2021
Data Generation for Neural Programming by Example AISTATS 2020
Barking up the right tree: an approach to search over molecule synthesis DAGs NIPS 2020
Goal-directed Generation of Discrete Structures with Conditional Generative Models NIPS 2020
Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models NIPS 2019
A Generative Model For Electron Paths ICLR 2019
A Model to Search for Synthesizable Molecules NIPS 2019
Structured Disentangled Representations AISTATS 2019
Learning a Generative Model for Validity in Complex Discrete Structures ICLR 2018
Grammar Variational Autoencoder ICML 2017
Learning Disentangled Representations with Semi-Supervised Deep Generative Models NIPS 2017
Interacting Particle Markov Chain Monte Carlo ICML 2016
Inference Networks for Sequential Monte Carlo in Graphical Models ICML 2016
Black-Box Policy Search with Probabilistic Programs AISTATS 2016
Asynchronous Anytime Sequential Monte Carlo NIPS 2014
A Compilation Target for Probabilistic Programming Languages ICML 2014
Bayesian Inference and Online Experimental Design for Mapping Neural Microcircuits NIPS 2013