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
David Alvarez-Melis
Senior Researcher
Papiers de Collaboration
-
-
-
-
A Label is Worth a Thousand Images in Dataset Distillation
Tian Qin, Zhiwei Deng, David Alvarez-Melis
NeurIPS 2024 | June 2024
-
Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains
Junhong Shen, Neil Tenenholtz, James Hall, David Alvarez-Melis, Nicolo Fusi
ICML 2024 | February 2024
-
-
-
InfoOT: Information Maximizing Optimal Transport
Ching-Yao Chuang, Stefanie Jegelka, David Alvarez-Melis
ICML 2023 | May 2023
-
-
-
Hierarchical Optimal Transport for Comparing Histopathology Datasets
Anna Yeaton, Rahul G Krishnan, Becky Mieloszyk, David Alvarez-Melis, Grace Huynh
April 2022
-
-
-
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
-
Dataset Dynamics via Gradient Flows in Probability Space
David Alvarez-Melis, Nicolo Fusi
ICML 2021 | July 2021
-
-
-
Gradient Flows in Dataset Space
David Alvarez-Melis, Nicolo Fusi
October 2020
-
Geometric Dataset Distances via Optimal Transport
David Alvarez-Melis, Nicolo Fusi
NeurIPS 2020 | February 2020
-
-
-
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
-
Towards Optimal Transport with Global Invariances
AISTATS | April 2019
-
Optimal transport in structured domains : algorithms and applications
March 2019
Thèse de doctorat : Massachusetts Institute of Technology | March 2019
-
-
-
Towards robust interpretability with self-explaining neural networks
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
-
-
-
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
-
A Label is Worth a Thousand Images in Dataset Distillation
Tian Qin, Zhiwei Deng, David Alvarez-Melis
NeurIPS 2024 | June 2024
-
Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains
Junhong Shen, Neil Tenenholtz, James Hall, David Alvarez-Melis, Nicolo Fusi
ICML 2024 | February 2024
-
InfoOT: Information Maximizing Optimal Transport
Ching-Yao Chuang, Stefanie Jegelka, David Alvarez-Melis
ICML 2023 | May 2023
-
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
-
Dataset Dynamics via Gradient Flows in Probability Space
David Alvarez-Melis, Nicolo Fusi
ICML 2021 | July 2021
-
Gradient Flows in Dataset Space
David Alvarez-Melis, Nicolo Fusi
October 2020
-
Geometric Dataset Distances via Optimal Transport
David Alvarez-Melis, Nicolo Fusi
NeurIPS 2020 | February 2020
-
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
-
Towards Optimal Transport with Global Invariances
AISTATS | April 2019
-
Towards robust interpretability with self-explaining neural networks
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
-
-
-
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
-
Hierarchical Optimal Transport for Comparing Histopathology Datasets
Anna Yeaton, Rahul G Krishnan, Becky Mieloszyk, David Alvarez-Melis, Grace Huynh
April 2022
-
-
-
Gradient Flows in Dataset Space
David Alvarez-Melis, Nicolo Fusi
October 2020
-
Geometric Dataset Distances via Optimal Transport
David Alvarez-Melis, Nicolo Fusi
NeurIPS 2020 | February 2020
-
Optimal transport in structured domains : algorithms and applications
March 2019
Thèse de doctorat : Massachusetts Institute of Technology | March 2019
-
-
-
-
-
A Label is Worth a Thousand Images in Dataset Distillation
Tian Qin, Zhiwei Deng, David Alvarez-Melis
NeurIPS 2024 | June 2024
-
Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains
Junhong Shen, Neil Tenenholtz, James Hall, David Alvarez-Melis, Nicolo Fusi
ICML 2024 | February 2024
-
InfoOT: Information Maximizing Optimal Transport
Ching-Yao Chuang, Stefanie Jegelka, David Alvarez-Melis
ICML 2023 | May 2023
-
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
-
Dataset Dynamics via Gradient Flows in Probability Space
David Alvarez-Melis, Nicolo Fusi
ICML 2021 | July 2021
-
Geometric Dataset Distances via Optimal Transport
David Alvarez-Melis, Nicolo Fusi
NeurIPS 2020 | February 2020
-
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
-
Towards Optimal Transport with Global Invariances
AISTATS | April 2019
-
Towards robust interpretability with self-explaining neural networks
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
-
-
-
Hierarchical Optimal Transport for Comparing Histopathology Datasets
Anna Yeaton, Rahul G Krishnan, Becky Mieloszyk, David Alvarez-Melis, Grace Huynh
April 2022
-
-
-
Optimal transport in structured domains : algorithms and applications
March 2019
Thèse de doctorat : Massachusetts Institute of Technology | March 2019
-