Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo. - Marton Havasi; José Miguel Hernández-Lobato; Juan José Murillo-Fuentes (NeurIPS, 2018)

Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters. - Marton Havasi; Robert Peharz; José Miguel Hernández-Lobato (ICLR (Poster), 2019)

Determining Optimal Coherency Interface for Many-Accelerator SoCs Using Bayesian Optimization. - Kshitij Bhardwaj; Marton Havasi; Yuan Yao 006; David M. Brooks; José Miguel Hernández-Lobato; Gu-Yeon Wei (IEEE Comput. Archit. Lett., 2019)

A comprehensive methodology to determine optimal coherence interfaces for many-accelerator SoCs. - Kshitij Bhardwaj; Marton Havasi; Yuan Yao 006; David M. Brooks; José Miguel Hernández-Lobato; Gu-Yeon Wei (ISLPED, 2020)

Compressing Images by Encoding Their Latent Representations with Relative Entropy Coding. - Gergely Flamich; Marton Havasi; José Miguel Hernández-Lobato (NeurIPS, 2020)

Training independent subnetworks for robust prediction. - Marton Havasi; Rodolphe Jenatton; Stanislav Fort; Jeremiah Zhe Liu; Jasper Snoek; Balaji Lakshminarayanan; Andrew Mingbo Dai; Dustin Tran (ICLR, 2021)

Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning. - Zachary Nado; Neil Band; Mark Collier; Josip Djolonga; Michael W. Dusenberry; Sebastian Farquhar; Angelos Filos; Marton Havasi; Rodolphe Jenatton; Ghassen Jerfel; Jeremiah Z. Liu; Zelda Mariet; et al. (CoRR, 2021)

Sampling the Variational Posterior with Local Refinement. - Marton Havasi; Jasper Snoek; Dustin Tran; Jonathan Gordon 003; José Miguel Hernández-Lobato (Entropy, 2021)

Learning Optimal Summaries of Clinical Time-series with Concept Bottleneck Models. - Carissa Wu; Sonali Parbhoo; Marton Havasi; Finale Doshi-Velez (MLHC, 2022)

Addressing Leakage in Concept Bottleneck Models. - Marton Havasi; Sonali Parbhoo; Finale Doshi-Velez (NeurIPS, 2022)

Does the explanation satisfy your needs?: A unified view of properties of explanations. - Zixi Chen; Varshini Subhash; Marton Havasi; Weiwei Pan; Finale Doshi-Velez (CoRR, 2022)

On improved Conditioning Mechanisms and Pre-training Strategies for Diffusion Models. - Tariq Berrada Ifriqi; Pietro Astolfi; Melissa Hall; Reyhane Askari Hemmat; Yohann Benchetrit; Marton Havasi; Matthew J. Muckley; Karteek Alahari; Adriana Romero-Soriano; Jakob Verbeek; Michal Drozdzal (NeurIPS, 2024)

Guarantee Regions for Local Explanations. - Marton Havasi; Sonali Parbhoo; Finale Doshi-Velez (CoRR, 2024)

Understanding and Mitigating Tokenization Bias in Language Models. - Buu Phan; Marton Havasi; Matthew J. Muckley; Karen Ullrich (CoRR, 2024)

On Improved Conditioning Mechanisms and Pre-training Strategies for Diffusion Models. - Tariq Berrada; Pietro Astolfi; Melissa Hall; Reyhane Askari Hemmat; Yohann Benchetrit; Marton Havasi; Matthew J. Muckley; Karteek Alahari; Adriana Romero-Soriano; Jakob Verbeek; Michal Drozdzal (CoRR, 2024)

Flow Matching Guide and Code. - Yaron Lipman; Marton Havasi; Peter Holderrieth; Neta Shaul; Matt Le 001; Brian Karrer; Ricky T. Q. Chen; David Lopez-Paz; Heli Ben-Hamu; Itai Gat (CoRR, 2024)

EvalGIM: A Library for Evaluating Generative Image Models. - Melissa Hall; Oscar Mañas; Reyhane Askari Hemmat; Mark Ibrahim; Candace Ross; Pietro Astolfi; Tariq Berrada Ifriqi; Marton Havasi; Yohann Benchetrit; Karen Ullrich; Carolina Braga; Abhishek Charnalia; et al. (CoRR, 2024)

Diverse Concept Proposals for Concept Bottleneck Models. - Katrina Brown; Marton Havasi; Finale Doshi-Velez (CoRR, 2024)

Architecture Optimizations for Improving Neural Image Compression Compute Complexity. - Matthew J. Muckley; Marton Havasi; Jakob Verbeek; Karen Ullrich (DCC, 2025)

Boosting Latent Diffusion with Perceptual Objectives. - Tariq Berrada; Pietro Astolfi; Melissa Hall; Marton Havasi; Yohann Benchetrit; Adriana Romero-Soriano; Karteek Alahari; Michal Drozdzal; Jakob Verbeek (ICLR, 2025)

Generator Matching: Generative modeling with arbitrary Markov processes. - Peter Holderrieth; Marton Havasi; Jason Yim; Neta Shaul; Itai Gat; Tommi S. Jaakkola; Brian Karrer; Ricky T. Q. Chen; Yaron Lipman (ICLR, 2025)

Exact Byte-Level Probabilities from Tokenized Language Models for FIM-Tasks and Model Ensembles. - Buu Phan; Brandon Amos; Itai Gat; Marton Havasi; Matthew J. Muckley; Karen Ullrich (ICLR, 2025)

Flow Matching with General Discrete Paths: A Kinetic-Optimal Perspective. - Neta Shaul; Itai Gat; Marton Havasi; Daniel Severo 001; Anuroop Sriram; Peter Holderrieth; Brian Karrer; Yaron Lipman; Ricky T. Q. Chen (ICLR, 2025)

Edit Flows: Flow Matching with Edit Operations. - Marton Havasi; Brian Karrer; Itai Gat; Ricky T. Q. Chen (CoRR, 2025)