Brooks Paige
25 papers · 2013–2025 · 4 conferences · across top CS/AI conferences
Achievements
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π Renaissance Researcher (5) π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (10) π§ Keyword Pioneer π Conference Polyglot (4)
π
Renaissance Researcher
(5)
π
Conference Polyglot
(4)
π
Academic Marathon
(12)
ποΈ
Keyword Collector
(106)
π
Century Club
(25)
π₯
Unstoppable
(10)
π
Trend Setter
π
Conference Pioneer
Conferences
NIPS (10)
ICML (7)
AISTATS (5)
ICLR (3)
Top co-authors
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