David Alvarez-Melis

Cituota

	Visi	Nuo 2020
Šaltiniai	3840	3380
h-rodyklė	20	20
i10-rodyklė	23	22

840

420

210

630

20172018201920202021202220232024202528 113 302 427 574 687 823 832 37

Viešas pasiekiamumas

Peržiūrėti viską

5 straipsniai

0 straipsnių

pasiekiami

nepasiekiami

Pagal finansavimo įpareigojimus

Bendraautoriai

Tommi JaakkolaMITPatvirtintas el. paštas csail.mit.edu
Nicolò FusiPartner Researcher, Microsoft ResearchPatvirtintas el. paštas microsoft.com
Stefanie JegelkaTUM and MITPatvirtintas el. paštas mit.edu
Jennifer Wortman VaughanSenior Principal Researcher, Microsoft Research, New York CityPatvirtintas el. paštas microsoft.com
Charlotte BunneProfessor of Computer Science and Life SciencesPatvirtintas el. paštas epfl.ch
Guang-He LeeMITPatvirtintas el. paštas mit.edu
Tatsunori HashimotoAssistant Professor, StanfordPatvirtintas el. paštas stanford.edu
Hanna WallachPartner Research Manager, Microsoft ResearchPatvirtintas el. paštas dirichlet.net
Hal Daumé IIIAssociate Professor of Computer Science, University of MarylandPatvirtintas el. paštas umiacs.umd.edu
Youssef MrouehPrincipal Research Scientist, IBM T.J Watson Research CenterPatvirtintas el. paštas us.ibm.com
Martin SaveskiAssistant Professor, University of WashingtonPatvirtintas el. paštas uw.edu
Andreas KrauseProfessor of Computer Science, ETH ZurichPatvirtintas el. paštas inf.ethz.ch
Neil TenenholtzMicrosoft ResearchPatvirtintas el. paštas microsoft.com
Yair SchiffCornell UniversityPatvirtintas el. paštas cs.cornell.edu
Grace HuynhMITPatvirtintas el. paštas mit.edu
Tian (Sunny) QinGraduate student, Harvard UniversityPatvirtintas el. paštas g.harvard.edu
Junhong ShenPh.D. student in Machine Learning, Carnegie Mellon UniversityPatvirtintas el. paštas andrew.cmu.edu
Suvrit SraTUM and MITPatvirtintas el. paštas mit.edu
Keyulu XuMITPatvirtintas el. paštas mit.edu
Chengtao LiGalixirPatvirtintas el. paštas galixir.com

Stebėti

David Alvarez-Melis

Harvard University & Microsoft Research

Patvirtintas el. paštas seas.harvard.edu - Pagrindinis puslapis

Machine Learning Optimal Transport Natural Language Processing Interpretability


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
Towards robust interpretability with self-explaining neural networks D Alvarez-Melis, TS Jaakkola Advances in Neural Information Processing Systems, 7775-7784, 2018	1157	2018
On the robustness of interpretability methods D Alvarez-Melis, TS Jaakkola Proceedings of the 2018 ICML Workshop on Human Interpretability in Machine …, 2018	741	2018
Gromov-Wasserstein alignment of word embedding spaces D Alvarez-Melis, TS Jaakkola Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018	353	2018
A causal framework for explaining the predictions of black-box sequence-to-sequence models D Alvarez-Melis, TS Jaakkola Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017	274	2017
Geometric Dataset Distances via Optimal Transport D Alvarez-Melis, N Fusi Advances in Neural Information Processing Systems 33, 21428--21439, 2020	216	2020
Topic Modeling in Twitter: Aggregating Tweets by Conversations. D Alvarez-Melis, M Saveski Proceedings of the Tenth International Conference on Web and Social Media …, 2016	187	2016
Learning generative models across incomparable spaces C Bunne, D Alvarez-Melis, A Krause, S Jegelka International conference on machine learning, 851-861, 2019	123	2019
Tree-structured decoding with doubly-recurrent neural networks D Alvarez-Melis, TS Jaakkola International Conference on Learning Representations (ICLR), 2017	111	2017
Word embeddings as metric recovery in semantic spaces TB Hashimoto, D Alvarez-Melis, TS Jaakkola Transactions of the Association for Computational Linguistics 4, 273-286, 2016	103	2016
Towards Optimal Transport with Global Invariances D Alvarez-Melis, S Jegelka, TS Jaakkola International Conference on Artificial Intelligence and Statistics (AISTATS), 2019	80	2019
Structured Optimal Transport D Alvarez-Melis, TS Jaakkola, S Jegelka International Conference on Artificial Intelligence and Statistics (AISTATS …, 2018	70	2018
Optimizing functionals on the space of probabilities with input convex neural networks D Alvarez-Melis, Y Schiff, Y Mroueh arXiv preprint arXiv:2106.00774, 2021	56	2021
Distributional adversarial networks C Li, D Alvarez-Melis, K Xu, S Jegelka, S Sra arXiv preprint arXiv:1706.09549, 2017	49*	2017
Towards robust, locally linear deep networks GH Lee, D Alvarez-Melis, TS Jaakkola International Conference on Learning Representations, 2019	48	2019
From human explanation to model interpretability: A framework based on weight of evidence DA Melis, H Kaur, H Daumé III, H Wallach, JW Vaughan Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 9 …, 2021	30	2021
Unsupervised hierarchy matching with optimal transport over hyperbolic spaces D Alvarez-Melis, Y Mroueh, T Jaakkola International Conference on Artificial Intelligence and Statistics, 1606-1617, 2020	29	2020
Weight of evidence as a basis for human-oriented explanations D Alvarez-Melis, H Daumé III, JW Vaughan, H Wallach arXiv preprint arXiv:1910.13503, 2019	25	2019
Functional transparency for structured data: a game-theoretic approach GH Lee, W Jin, D Alvarez-Melis, T Jaakkola International Conference on Machine Learning, 3723-3733, 2019	23	2019
Dataset dynamics via gradient flows in probability space D Alvarez-Melis, N Fusi International conference on machine learning, 219-230, 2021	22	2021
Neural unbalanced optimal transport via cycle-consistent semi-couplings F Lübeck, C Bunne, G Gut, JS del Castillo, L Pelkmans, D Alvarez-Melis arXiv preprint arXiv:2209.15621, 2022	21	2022

Sistema negali atlikti operacijos. Bandykite vėliau dar kartą.

Straipsniai 1–20

Šaltinių per metus

Dubliuoti šaltiniai

Sujungti šaltiniai

Pridėti bendraautoriusBendraautoriai

Stebėti

Cituota

Bendraautoriai