Matthew D. Hoffman

American Foundry Society — United States

Computer Science · Physical Sciences

33h-index17.7kcitations113works1.92yr avg
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Research Topics

Gaussian Processes and Bayesian Inference(28), Music and Audio Processing(24), Bayesian Methods and Mixture Models(20), Markov Chains and Monte Carlo Methods(17), Generative Adversarial Networks and Image Synthesis(16)

Publications113 total

The Impacts of Adaptive Learning Technologies on K-12 Teachers’ Sense of Autonomy, Competence, and Relatedness with Their Students
2025Open Access
Running Markov Chain Monte Carlo on Modern Hardware and Software
arXiv (Cornell University)·2024Open Access
Selectivity of Ru and Fe P<sup>R</sup><sub>2</sub>N<sup>R’</sup><sub>2</sub> Catalysts Toward Acceptorless Dehydrogenation of Benzylamine
Organometallics·2024· 2 cited
Scalable spatiotemporal prediction with Bayesian neural fields
Nature Communications·2024· 13 citedOpen Access
Distance Learning LDRD: Using Latent Deep Learning Distances to Create Trusted Models
2024Open Access
HaMLET: Human and Machine Learning Effective Teaming
2024Open Access
Nested Rˆ: Assessing the Convergence of Markov Chain Monte Carlo When Running Many Short Chains
Bayesian Analysis·2024· 6 citedOpen Access
Scalable Spatiotemporal Prediction with Bayesian Neural Fields
arXiv (Cornell University)·2024Open Access
Reply on RC1
2024Open Access
Reply on RC2
2024Open Access
Robust Inverse Graphics via Probabilistic Inference
arXiv (Cornell University)·2024Open Access
Training Chain-of-Thought via Latent-Variable Inference
arXiv (Cornell University)·2023· 2 citedOpen Access
Sequential Monte Carlo Learning for Time Series Structure Discovery
arXiv (Cornell University)·2023· 2 citedOpen Access
Impact of Arteriovenous Fistula Compression on Mitral Regurgitation Severity
Circulation Heart Failure·2023Open Access
Catalyst Comparison for Additive-Free Acceptorless Dehydrogenation of Indoline Derivatives
Synlett·2023· 1 cited
ProbNeRF: Uncertainty-Aware Inference of 3D Shapes from 2D Images
arXiv (Cornell University)·2022· 4 citedOpen Access
Lossy Compression with Gaussian Diffusion
arXiv (Cornell University)·2022· 20 citedOpen Access
Nested $\hat R$: Assessing Convergence for Markov chain Monte Carlo when using many short chains.
arXiv (Cornell University)·2021Open Access
Nested $\hat R$: Assessing the convergence of Markov chain Monte Carlo when running many short chains
arXiv (Cornell University)·2021· 1 citedOpen Access
What Are Bayesian Neural Network Posteriors Really Like
International Conference on Machine Learning·2021· 32 cited
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Frequent Co-authors

David M. Blei(13), Perry R. Cook(5), Dawen Liang(4), Stephan Mandt(4), Nando de Freitas(4), Dustin Tran(4), Rif A. Saurous(4), Michael Betancourt(3), Marcus A. Brubaker(3), Peter Li(3), Rahul G. Krishnan(3), Cheng-Zhi Anna Huang(3), Ashish Vaswani(3), Jakob Uszkoreit(3), Noam Shazeer(3), Curtis Hawthorne(3), Andrew M. Dai(3), Douglas Eck(3), Bob Carpenter(2), Andrew Gelman(2)