Marton Havasi - RankMe

34 papers A* 9A 1B 1Journal 21Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	B	`conf`	Architecture Optimizations for Improving Neural Image Compression Compute Complexity. DCC Matthew J. Muckley, Marton Havasi, Jakob Verbeek, Karen Ullrich
2025	A*	`conf`	Boosting Latent Diffusion with Perceptual Objectives. ICLR Tariq Berrada, Pietro Astolfi, Melissa Hall, Marton Havasi, Yohann Benchetrit, Adriana Romero-Soriano, Karteek Alahari, Michal Drozdzal, Jakob Verbeek
2025	J	`jnl`	Edit Flows: Flow Matching with Edit Operations. CoRR Marton Havasi, Brian Karrer, Itai Gat, Ricky T. Q. Chen
2025	A*	`conf`	Exact Byte-Level Probabilities from Tokenized Language Models for FIM-Tasks and Model Ensembles. ICLR Buu Phan, Brandon Amos, Itai Gat, Marton Havasi, Matthew J. Muckley, Karen Ullrich
2025	A*	`conf`	Flow Matching with General Discrete Paths: A Kinetic-Optimal Perspective. ICLR Neta Shaul, Itai Gat, Marton Havasi, Daniel Severo, Anuroop Sriram, Peter Holderrieth, Brian Karrer, Yaron Lipman, Ricky T. Q. Chen
2025	A*	`conf`	Generator Matching: Generative modeling with arbitrary Markov processes. ICLR Peter Holderrieth, Marton Havasi, Jason Yim, Neta Shaul, Itai Gat, Tommi S. Jaakkola, Brian Karrer, Ricky T. Q. Chen, Yaron Lipman
2025	J	`jnl`	OneFlow: Concurrent Mixed-Modal and Interleaved Generation with Edit Flows. CoRR John Nguyen, Marton Havasi, Tariq Berrada, Luke Zettlemoyer, Ricky T. Q. Chen
2025	J	`jnl`	Set Block Decoding is a Language Model Inference Accelerator. CoRR Itai Gat, Heli Ben-Hamu, Marton Havasi, Daniel Haziza, Jeremy Reizenstein, Gabriel Synnaeve, David Lopez-Paz, Brian Karrer, Yaron Lipman
2024	J	`jnl`	Boosting Latent Diffusion with Perceptual Objectives. CoRR Tariq Berrada, Pietro Astolfi, Jakob Verbeek, Melissa Hall, Marton Havasi, Michal Drozdzal, Yohann Benchetrit, Adriana Romero-Soriano, Karteek Alahari
2024	J	`jnl`	Diverse Concept Proposals for Concept Bottleneck Models. CoRR Katrina Brown, Marton Havasi, Finale Doshi-Velez
2024	J	`jnl`	EvalGIM: A Library for Evaluating Generative Image Models. CoRR 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, Maeve Ryan, Mike Rabbat, Michal Drozdzal, Jakob Verbeek, Adriana Romero-Soriano
2024	J	`jnl`	Exact Byte-Level Probabilities from Tokenized Language Models for FIM-Tasks and Model Ensembles. CoRR Buu Phan, Brandon Amos, Itai Gat, Marton Havasi, Matthew J. Muckley, Karen Ullrich
2024	J	`jnl`	Flow Matching Guide and Code. CoRR Yaron Lipman, Marton Havasi, Peter Holderrieth, Neta Shaul, Matt Le, Brian Karrer, Ricky T. Q. Chen, David Lopez-Paz, Heli Ben-Hamu, Itai Gat
2024	J	`jnl`	Flow Matching with General Discrete Paths: A Kinetic-Optimal Perspective. CoRR Neta Shaul, Itai Gat, Marton Havasi, Daniel Severo, Anuroop Sriram, Peter Holderrieth, Brian Karrer, Yaron Lipman, Ricky T. Q. Chen
2024	J	`jnl`	Generator Matching: Generative modeling with arbitrary Markov processes. CoRR Peter Holderrieth, Marton Havasi, Jason Yim, Neta Shaul, Itai Gat, Tommi S. Jaakkola, Brian Karrer, Ricky T. Q. Chen, Yaron Lipman
2024	J	`jnl`	Guarantee Regions for Local Explanations. CoRR Marton Havasi, Sonali Parbhoo, Finale Doshi-Velez
2024	J	`jnl`	On Improved Conditioning Mechanisms and Pre-training Strategies for Diffusion Models. CoRR 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
2024	A*	`conf`	On improved Conditioning Mechanisms and Pre-training Strategies for Diffusion Models. NeurIPS 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
2024	J	`jnl`	Understanding and Mitigating Tokenization Bias in Language Models. CoRR Buu Phan, Marton Havasi, Matthew J. Muckley, Karen Ullrich
2022	A*	`conf`	Addressing Leakage in Concept Bottleneck Models. NeurIPS Marton Havasi, Sonali Parbhoo, Finale Doshi-Velez
2022	J	`jnl`	Does the explanation satisfy your needs?: A unified view of properties of explanations. CoRR Zixi Chen, Varshini Subhash, Marton Havasi, Weiwei Pan, Finale Doshi-Velez
2022	—	`conf`	Learning Optimal Summaries of Clinical Time-series with Concept Bottleneck Models. MLHC Carissa Wu, Sonali Parbhoo, Marton Havasi, Finale Doshi-Velez
2021	J	`jnl`	Sampling the Variational Posterior with Local Refinement. Entropy Marton Havasi, Jasper Snoek, Dustin Tran, Jonathan Gordon, José Miguel Hernández-Lobato
2021	A*	`conf`	Training independent subnetworks for robust prediction. ICLR Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu, Jasper Snoek, Balaji Lakshminarayanan, Andrew Mingbo Dai, Dustin Tran
2021	J	`jnl`	Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning. CoRR 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, Jeremy Nixon, Shreyas Padhy, Jie Ren, Tim G. J. Rudner, Yeming Wen, Florian Wenzel, Kevin Murphy, D. Sculley, Balaji Lakshminarayanan, Jasper Snoek, Yarin Gal, Dustin Tran
2020	A	`conf`	A comprehensive methodology to determine optimal coherence interfaces for many-accelerator SoCs. ISLPED Kshitij Bhardwaj, Marton Havasi, Yuan Yao, David M. Brooks, José Miguel Hernández-Lobato, Gu-Yeon Wei
2020	A*	`conf`	Compressing Images by Encoding Their Latent Representations with Relative Entropy Coding. NeurIPS Gergely Flamich, Marton Havasi, José Miguel Hernández-Lobato
2020	J	`jnl`	Compressing Images by Encoding Their Latent Representations with Relative Entropy Coding. CoRR Gergely Flamich, Marton Havasi, José Miguel Hernández-Lobato
2020	J	`jnl`	Training independent subnetworks for robust prediction. CoRR Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu, Jasper Snoek, Balaji Lakshminarayanan, Andrew M. Dai, Dustin Tran
2019	J	`jnl`	Determining Optimal Coherency Interface for Many-Accelerator SoCs Using Bayesian Optimization. IEEE Comput. Archit. Lett. Kshitij Bhardwaj, Marton Havasi, Yuan Yao, David M. Brooks, José Miguel Hernández-Lobato, Gu-Yeon Wei
2019	—	`conf`	Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters. ICLR (Poster) Marton Havasi, Robert Peharz, José Miguel Hernández-Lobato
2018	A*	`conf`	Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo. NeurIPS Marton Havasi, José Miguel Hernández-Lobato, Juan José Murillo-Fuentes
2018	J	`jnl`	Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo. CoRR Marton Havasi, José Miguel Hernández-Lobato, Juan José Murillo-Fuentes
2018	J	`jnl`	Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters. CoRR Marton Havasi, Robert Peharz, José Miguel Hernández-Lobato