Brooks Paige

Orcid: 0000-0002-4797-1563

According to our database1, Brooks Paige authored at least 48 papers between 2013 and 2024.

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Bibliography

2024
Right Now, Wrong Then: Non-Stationary Direct Preference Optimization under Preference Drift.
CoRR, 2024

AsEP: Benchmarking Deep Learning Methods for Antibody-specific Epitope Prediction.
CoRR, 2024

Analyzing the Generalization and Reliability of Steering Vectors.
CoRR, 2024

Generative Active Learning for the Search of Small-molecule Protein Binders.
CoRR, 2024

Can a Confident Prior Replace a Cold Posterior?
CoRR, 2024

Diffusive Gibbs Sampling.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Gaussian Processes on Cellular Complexes.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Explaining holistic image regressors and classifiers in urban analytics with plausible counterfactuals.
Int. J. Geogr. Inf. Sci., December, 2023

Moment Matching Denoising Gibbs Sampling.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Towards Healing the Blindness of Score Matching.
CoRR, 2022

Improving VAE-based Representation Learning.
CoRR, 2022

Fast and Scalable Spike and Slab Variable Selection in High-Dimensional Gaussian Processes.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Reconstructing Genotypes in Private Genomic Databases from Genetic Risk Scores.
J. Comput. Biol., May, 2021

Simulation Intelligence: Towards a New Generation of Scientific Methods.
CoRR, 2021

I Don't Need u: Identifiable Non-Linear ICA Without Side Information.
CoRR, 2021

Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models.
Proceedings of the 9th International Conference on Learning Representations, 2021

Learning Bijective Feature Maps for Linear ICA.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Bayesian Graph Neural Networks for Molecular Property Prediction.
CoRR, 2020

Making Graph Neural Networks Worth It for Low-Data Molecular Machine Learning.
CoRR, 2020

Goal-directed Generation of Discrete Structures with Conditional Generative Models.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Barking up the right tree: an approach to search over molecule synthesis DAGs.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Data Generation for Neural Programming by Example.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Take a Look Around: Using Street View and Satellite Images to Estimate House Prices.
ACM Trans. Intell. Syst. Technol., 2019

Usability of Probabilistic Programming Languages.
Proceedings of the 30th Annual Workshop of the Psychology of Programming Interest Group, 2019

Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Model to Search for Synthesizable Molecules.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Generating Molecules via Chemical Reactions.
Proceedings of the Deep Generative Models for Highly Structured Data, 2019

A Generative Model For Electron Paths.
Proceedings of the 7th International Conference on Learning Representations, 2019

Structured Disentangled Representations.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
An Introduction to Probabilistic Programming.
CoRR, 2018

Predicting Electron Paths.
CoRR, 2018

Hierarchical Disentangled Representations.
CoRR, 2018

Learning a Generative Model for Validity in Complex Discrete Structures.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
Kernel Sequential Monte Carlo.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Learning Disentangled Representations with Semi-Supervised Deep Generative Models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Grammar Variational Autoencoder.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Inducing Interpretable Representations with Variational Autoencoders.
CoRR, 2016

Probabilistic structure discovery in time series data.
CoRR, 2016

Super-Sampling with a Reservoir.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Interacting Particle Markov Chain Monte Carlo.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Inference Networks for Sequential Monte Carlo in Graphical Models.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Black-Box Policy Search with Probabilistic Programs.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Path Finding under Uncertainty through Probabilistic Inference.
CoRR, 2015

Adaptive Scheduling in MCMC and Probabilistic Programming.
CoRR, 2015

Output-Sensitive Adaptive Metropolis-Hastings for Probabilistic Programs.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

2014
Asynchronous Anytime Sequential Monte Carlo.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

A Compilation Target for Probabilistic Programming Languages.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
Bayesian Inference and Online Experimental Design for Mapping Neural Microcircuits.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013


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