David Alvarez-Melis

Senior Researcher

Publications

Afficher par:

- KerJEPA: Kernel Discrepancies for Euclidean Self-Supervised Learning
  
  Eric Zimmermann, Eric Zimmermann, Harley Wiltzer, Justin Szeto, David Alvarez-Melis, Lester Mackey
  
  December 2025
  
  Publication
- scGeneScope: A Treatment-Matched Single Cell Imaging and Transcriptomics Dataset and Benchmark for Treatment Response Modeling
  
  Joel Dapello, Marcel Nassar, Ridvan Eksi, Ban Wang, Jules Gagnon-Marchand, Kenneth Gao, akram Baharlouei, Kyra Thrush, Nina Riehs, Amy Peterson, Aniket Tolpadi, Abhejit Rajagopal, Henry Miller, ashley conard, David Alvarez-Melis, Rory Stark, Simone Bianco, Morgan Levine, Ava P. Amini, Alex Lu, Nicolo Fusi, Ravi Pandya, Valentina Pedoia, Hana El-Samad
  
  NeurIPS 2025 | October 2025
  
  Publication
- Causal integration of chemical structures improves representations of microscopy images for morphological profiling
  
  Yemin Yu, Neil Tenenholtz, Lester Mackey, Ying Wei, David Alvarez-Melis, Ava P. Amini, Alex Lu
  
  April 2025
  
  DOI Publication Publication Github
- A Label is Worth a Thousand Images in Dataset Distillation
  
  Tian Qin, Zhiwei Deng, David Alvarez-Melis
  
  NeurIPS 2024 | June 2024
  
  DOI Publication Publication
- Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains
  
  Junhong Shen, Neil Tenenholtz, James Hall, David Alvarez-Melis, Nicolo Fusi
  
  ICML 2024 | February 2024
  
  DOI Publication Publication
- InfoOT: Information Maximizing Optimal Transport
  
  Ching-Yao Chuang, Stefanie Jegelka, David Alvarez-Melis
  
  ICML 2023 | May 2023
  
  Publication
- Hierarchical Optimal Transport for Comparing Histopathology Datasets
  
  Anna Yeaton, Rahul G Krishnan, Becky Mieloszyk, David Alvarez-Melis, Grace Huynh
  
  April 2022
  
  Publication
- From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence
  
  David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna Wallach, Jennifer Wortman Vaughan
  
  HCOMP 2021 | September 2021
  
  Publication Projet
- Dataset Dynamics via Gradient Flows in Probability Space
  
  David Alvarez-Melis, Nicolo Fusi
  
  ICML 2021 | July 2021
  
  Publication
- Gradient Flows in Dataset Space
  
  David Alvarez-Melis, Nicolo Fusi
  
  October 2020
  
  Publication Projet
- Geometric Dataset Distances via Optimal Transport
  
  David Alvarez-Melis, Nicolo Fusi
  
  NeurIPS 2020 | February 2020
  
  PDF Projet
- Weight of Evidence as a Basis for Human-Oriented Explanations
  
  David Alvarez-Melis, Hal Daumé III, Jennifer Wortman Vaughan, Hanna Wallach
  
  Workshop on Human-Centric Machine Learning at the 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada. | October 2019
  
  Publication
- Towards Optimal Transport with Global Invariances
  
  David Alvarez-Melis
  
  AISTATS | April 2019
  
  PDF Publication Publication Publication
- Optimal transport in structured domains : algorithms and applications
  
  David Alvarez-Melis
  
  March 2019
  
  Thèse de doctorat : Massachusetts Institute of Technology | March 2019
  
  Publication
- Towards robust interpretability with self-explaining neural networks
  
  David Alvarez-Melis
  
  NeurIPS 2018 | December 2018
  
  PDF PDF Publication Publication Publication Publication Publication
- On the Robustness of Interpretability Methods
  
  David Alvarez-Melis, Tommi S. Jaakkola
  
  WHI 2018 | June 2018
  
  Publication

- KerJEPA: Kernel Discrepancies for Euclidean Self-Supervised Learning
  
  Eric Zimmermann, Eric Zimmermann, Harley Wiltzer, Justin Szeto, David Alvarez-Melis, Lester Mackey
  
  December 2025
  
  Publication
- Causal integration of chemical structures improves representations of microscopy images for morphological profiling
  
  Yemin Yu, Neil Tenenholtz, Lester Mackey, Ying Wei, David Alvarez-Melis, Ava P. Amini, Alex Lu
  
  April 2025
  
  DOI Publication Publication Github
- A Label is Worth a Thousand Images in Dataset Distillation
  
  Tian Qin, Zhiwei Deng, David Alvarez-Melis
  
  NeurIPS 2024 | June 2024
  
  DOI Publication Publication
- Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains
  
  Junhong Shen, Neil Tenenholtz, James Hall, David Alvarez-Melis, Nicolo Fusi
  
  ICML 2024 | February 2024
  
  DOI Publication Publication
- InfoOT: Information Maximizing Optimal Transport
  
  Ching-Yao Chuang, Stefanie Jegelka, David Alvarez-Melis
  
  ICML 2023 | May 2023
  
  Publication
- From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence
  
  David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna Wallach, Jennifer Wortman Vaughan
  
  HCOMP 2021 | September 2021
  
  Publication Projet
- Dataset Dynamics via Gradient Flows in Probability Space
  
  David Alvarez-Melis, Nicolo Fusi
  
  ICML 2021 | July 2021
  
  Publication
- Gradient Flows in Dataset Space
  
  David Alvarez-Melis, Nicolo Fusi
  
  October 2020
  
  Publication Projet
- Geometric Dataset Distances via Optimal Transport
  
  David Alvarez-Melis, Nicolo Fusi
  
  NeurIPS 2020 | February 2020
  
  PDF Projet
- Weight of Evidence as a Basis for Human-Oriented Explanations
  
  David Alvarez-Melis, Hal Daumé III, Jennifer Wortman Vaughan, Hanna Wallach
  
  Workshop on Human-Centric Machine Learning at the 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada. | October 2019
  
  Publication
- Towards Optimal Transport with Global Invariances
  
  David Alvarez-Melis
  
  AISTATS | April 2019
  
  PDF Publication Publication Publication
- Towards robust interpretability with self-explaining neural networks
  
  David Alvarez-Melis
  
  NeurIPS 2018 | December 2018
  
  PDF PDF Publication Publication Publication Publication Publication
- On the Robustness of Interpretability Methods
  
  David Alvarez-Melis, Tommi S. Jaakkola
  
  WHI 2018 | June 2018
  
  Publication
- scGeneScope: A Treatment-Matched Single Cell Imaging and Transcriptomics Dataset and Benchmark for Treatment Response Modeling
  
  Joel Dapello, Marcel Nassar, Ridvan Eksi, Ban Wang, Jules Gagnon-Marchand, Kenneth Gao, akram Baharlouei, Kyra Thrush, Nina Riehs, Amy Peterson, Aniket Tolpadi, Abhejit Rajagopal, Henry Miller, ashley conard, David Alvarez-Melis, Rory Stark, Simone Bianco, Morgan Levine, Ava P. Amini, Alex Lu, Nicolo Fusi, Ravi Pandya, Valentina Pedoia, Hana El-Samad
  
  NeurIPS 2025 | October 2025
  
  Publication
- Causal integration of chemical structures improves representations of microscopy images for morphological profiling
  
  Yemin Yu, Neil Tenenholtz, Lester Mackey, Ying Wei, David Alvarez-Melis, Ava P. Amini, Alex Lu
  
  April 2025
  
  DOI Publication Publication Github
- Hierarchical Optimal Transport for Comparing Histopathology Datasets
  
  Anna Yeaton, Rahul G Krishnan, Becky Mieloszyk, David Alvarez-Melis, Grace Huynh
  
  April 2022
  
  Publication
- Gradient Flows in Dataset Space
  
  David Alvarez-Melis, Nicolo Fusi
  
  October 2020
  
  Publication Projet
- Geometric Dataset Distances via Optimal Transport
  
  David Alvarez-Melis, Nicolo Fusi
  
  NeurIPS 2020 | February 2020
  
  PDF Projet
- Optimal transport in structured domains : algorithms and applications
  
  David Alvarez-Melis
  
  March 2019
  
  Thèse de doctorat : Massachusetts Institute of Technology | March 2019
  
  Publication
- Gradient Flows in Dataset Space
  
  David Alvarez-Melis, Nicolo Fusi
  
  October 2020
  
  Publication Projet

- KerJEPA: Kernel Discrepancies for Euclidean Self-Supervised Learning
  
  Eric Zimmermann, Eric Zimmermann, Harley Wiltzer, Justin Szeto, David Alvarez-Melis, Lester Mackey
  
  December 2025
  
  Publication
- Causal integration of chemical structures improves representations of microscopy images for morphological profiling
  
  Yemin Yu, Neil Tenenholtz, Lester Mackey, Ying Wei, David Alvarez-Melis, Ava P. Amini, Alex Lu
  
  April 2025
  
  DOI Publication Publication Github
- Gradient Flows in Dataset Space
  
  David Alvarez-Melis, Nicolo Fusi
  
  October 2020
  
  Publication Projet
- scGeneScope: A Treatment-Matched Single Cell Imaging and Transcriptomics Dataset and Benchmark for Treatment Response Modeling
  
  Joel Dapello, Marcel Nassar, Ridvan Eksi, Ban Wang, Jules Gagnon-Marchand, Kenneth Gao, akram Baharlouei, Kyra Thrush, Nina Riehs, Amy Peterson, Aniket Tolpadi, Abhejit Rajagopal, Henry Miller, ashley conard, David Alvarez-Melis, Rory Stark, Simone Bianco, Morgan Levine, Ava P. Amini, Alex Lu, Nicolo Fusi, Ravi Pandya, Valentina Pedoia, Hana El-Samad
  
  NeurIPS 2025 | October 2025
  
  Publication
- A Label is Worth a Thousand Images in Dataset Distillation
  
  Tian Qin, Zhiwei Deng, David Alvarez-Melis
  
  NeurIPS 2024 | June 2024
  
  DOI Publication Publication
- Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains
  
  Junhong Shen, Neil Tenenholtz, James Hall, David Alvarez-Melis, Nicolo Fusi
  
  ICML 2024 | February 2024
  
  DOI Publication Publication
- InfoOT: Information Maximizing Optimal Transport
  
  Ching-Yao Chuang, Stefanie Jegelka, David Alvarez-Melis
  
  ICML 2023 | May 2023
  
  Publication
- From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence
  
  David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna Wallach, Jennifer Wortman Vaughan
  
  HCOMP 2021 | September 2021
  
  Publication Projet
- Dataset Dynamics via Gradient Flows in Probability Space
  
  David Alvarez-Melis, Nicolo Fusi
  
  ICML 2021 | July 2021
  
  Publication
- Geometric Dataset Distances via Optimal Transport
  
  David Alvarez-Melis, Nicolo Fusi
  
  NeurIPS 2020 | February 2020
  
  PDF Projet
- Weight of Evidence as a Basis for Human-Oriented Explanations
  
  David Alvarez-Melis, Hal Daumé III, Jennifer Wortman Vaughan, Hanna Wallach
  
  Workshop on Human-Centric Machine Learning at the 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada. | October 2019
  
  Publication
- Towards Optimal Transport with Global Invariances
  
  David Alvarez-Melis
  
  AISTATS | April 2019
  
  PDF Publication Publication Publication
- Towards robust interpretability with self-explaining neural networks
  
  David Alvarez-Melis
  
  NeurIPS 2018 | December 2018
  
  PDF PDF Publication Publication Publication Publication Publication
- On the Robustness of Interpretability Methods
  
  David Alvarez-Melis, Tommi S. Jaakkola
  
  WHI 2018 | June 2018
  
  Publication
- Hierarchical Optimal Transport for Comparing Histopathology Datasets
  
  Anna Yeaton, Rahul G Krishnan, Becky Mieloszyk, David Alvarez-Melis, Grace Huynh
  
  April 2022
  
  Publication
- Optimal transport in structured domains : algorithms and applications
  
  David Alvarez-Melis
  
  March 2019
  
  Thèse de doctorat : Massachusetts Institute of Technology | March 2019
  
  Publication

David Alvarez-Melis

Publications

KerJEPA: Kernel Discrepancies for Euclidean Self-Supervised Learning

scGeneScope: A Treatment-Matched Single Cell Imaging and Transcriptomics Dataset and Benchmark for Treatment Response Modeling

Causal integration of chemical structures improves representations of microscopy images for morphological profiling

A Label is Worth a Thousand Images in Dataset Distillation

Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains

InfoOT: Information Maximizing Optimal Transport

Hierarchical Optimal Transport for Comparing Histopathology Datasets

From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence

Dataset Dynamics via Gradient Flows in Probability Space

Gradient Flows in Dataset Space

Geometric Dataset Distances via Optimal Transport

Weight of Evidence as a Basis for Human-Oriented Explanations

Towards Optimal Transport with Global Invariances

Optimal transport in structured domains : algorithms and applications

Towards robust interpretability with self-explaining neural networks

On the Robustness of Interpretability Methods

KerJEPA: Kernel Discrepancies for Euclidean Self-Supervised Learning

Causal integration of chemical structures improves representations of microscopy images for morphological profiling

A Label is Worth a Thousand Images in Dataset Distillation

Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains

InfoOT: Information Maximizing Optimal Transport

From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence

Dataset Dynamics via Gradient Flows in Probability Space

Gradient Flows in Dataset Space

Geometric Dataset Distances via Optimal Transport

Weight of Evidence as a Basis for Human-Oriented Explanations

Towards Optimal Transport with Global Invariances

Towards robust interpretability with self-explaining neural networks

On the Robustness of Interpretability Methods

scGeneScope: A Treatment-Matched Single Cell Imaging and Transcriptomics Dataset and Benchmark for Treatment Response Modeling

Causal integration of chemical structures improves representations of microscopy images for morphological profiling

Hierarchical Optimal Transport for Comparing Histopathology Datasets

Gradient Flows in Dataset Space

Geometric Dataset Distances via Optimal Transport

Optimal transport in structured domains : algorithms and applications

Gradient Flows in Dataset Space

KerJEPA: Kernel Discrepancies for Euclidean Self-Supervised Learning

Causal integration of chemical structures improves representations of microscopy images for morphological profiling

Gradient Flows in Dataset Space

scGeneScope: A Treatment-Matched Single Cell Imaging and Transcriptomics Dataset and Benchmark for Treatment Response Modeling

A Label is Worth a Thousand Images in Dataset Distillation

Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains

InfoOT: Information Maximizing Optimal Transport

From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence

Dataset Dynamics via Gradient Flows in Probability Space

Geometric Dataset Distances via Optimal Transport

Weight of Evidence as a Basis for Human-Oriented Explanations

Towards Optimal Transport with Global Invariances

Towards robust interpretability with self-explaining neural networks

On the Robustness of Interpretability Methods

Hierarchical Optimal Transport for Comparing Histopathology Datasets

Optimal transport in structured domains : algorithms and applications