Joshua Robinson

Cited by

	All	Since 2019
Citations	1843	1841
h-index	11	11
i10-index	11	11

620

310

155

465

2020202120222023202417 172 418 612 616

Public access

View all

7 articles

0 articles

available

not available

Based on funding mandates

Co-authors

Stefanie JegelkaTUM and MITVerified email at mit.edu
Suvrit SraTUM and MITVerified email at mit.edu
Ching-Yao ChuangMeta GenAI, MITVerified email at meta.com
Derek LimMITVerified email at mit.edu
Antonio TorralbaProfessor of Computer Science, MITVerified email at csail.mit.edu
Haggai MaronAssistant Professor at the Technion, Research Scientist at NVIDIA ResearchVerified email at technion.ac.il
Kayhan BatmanghelichAssistant Professor, Boston UniversityVerified email at bu.edu
Dilip KrishnanResearch Scientist, GoogleVerified email at google.com
Jure LeskovecProfessor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Robert MacKayProfessor of Mathematics, University of WarwickVerified email at warwick.ac.uk
Karalias NikolaosMITVerified email at mit.edu
Andreas LoukasSenior Principal Scientist, Prescient Design, gRED, RocheVerified email at roche.com
Sharut GuptaMassachusetts Institute of TechnologyVerified email at mit.edu

Joshua Robinson

Stanford

Verified email at mit.edu - Homepage

machine learning geometric deep learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Contrastive learning with hard negative samples J Robinson, CY Chuang, S Sra, S Jegelka ICLR, 2021	795	2021
Debiased contrastive learning CY Chuang, J Robinson, L Yen-Chen, A Torralba, S Jegelka NeurIPS, 2020	628	2020
Sign and basis invariant networks for spectral graph representation learning D Lim, J Robinson, L Zhao, T Smidt, SJ Suvrit Sra, Haggai Maron ICLR, 2023	134	2023
Can contrastive learning avoid shortcut solutions? J Robinson, L Sun, K Yu, K Batmanghelich, S Jegelka, S Sra NeurIPS, 2021	127	2021
Strength from Weakness: Fast Learning Using Weak Supervision J Robinson, S Jegelka, S Sra ICML, 2020	43	2020
A simple, efficient and scalable contrastive masked autoencoder for learning visual representations S Mishra, J Robinson, H Chang, D Jacobs, A Sarna, A Maschinot, ... Technical Report, 2022	25	2022
Aggregation of Markov flows I: theory R MacKay, J Robinson Philosophical Transactions of the Royal Society A: Mathematical, Physical …, 2018	25	2018
On the Stability of Expressive Positional Encodings for Graph Neural Networks Y Huang, W Lu, J Robinson, Y Yang, M Zhang, S Jegelka, P Li ICLR, 2024	15	2024
Flexible modeling of diversity with strongly log-concave distributions J Robinson, S Sra, S Jegelka NeurIPS, 2019	14	2019
Expressive Sign Equivariant Networks for Spectral Geometric Learning D Lim, J Robinson, S Jegelka, Y Lipman, H Maron NeurIPS, 2023	12	2023
Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning S Gupta, J Robinson, D Lim, S Villar, S Jegelka ICLR, 2024	11	2024
Relational Deep Learning: Graph Representation Learning on Relational Databases M Fey, W Hu, K Huang, JE Lenssen, R Ranjan, J Robinson, R Ying, J You, ... ICML Position Paper, 2023	7*	2023
Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions N Karalias, J Robinson, A Loukas, S Jegelka NeurIPS, 2022	7	2022
RelBench: A Benchmark for Deep Learning on Relational Databases J Robinson, R Ranjan, W Hu, K Huang, J Han, A Dobles, M Fey, ... arXiv preprint arXiv:2407.20060, 2024		2024
The First Learning on Graphs Conference: Preface B Rieck, R Pascanu, Y Du, H Stärk, D Lim, CK Joshi, A Deac, I Duta, ... Learning on Graphs Conference, i-xxiii, 2022		2022

The system can't perform the operation now. Try again later.

Articles 1–15

Citations per year

Duplicate citations

Merged citations

Add co-authorsCo-authors

Follow

Cited by

Co-authors