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Yuge Shi
ORCID
Publication Activity (10 Years)
Years Active: 2018-2024
Publications (10 Years): 17
Top Topics
Feature Mapping
Generative Model
Uni Modal
Supervised Learning
Top Venues
CoRR
ICLR
ICML
ECCV (10)
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Publications
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Ivana Balazevic
,
Yuge Shi
,
Pinelopi Papalampidi
,
Rahma Chaabouni
,
Skanda Koppula
,
Olivier J. Hénaff
Memory Consolidation Enables Long-Context Video Understanding.
CoRR
(2024)
André Susano Pinto
,
Alexander Kolesnikov
,
Yuge Shi
,
Lucas Beyer
,
Xiaohua Zhai
Tuning computer vision models with task rewards.
CoRR
(2023)
Yuge Shi
,
Imant Daunhawer
,
Julia E. Vogt
,
Philip H. S. Torr
,
Amartya Sanyal
How robust is unsupervised representation learning to distribution shift?
ICLR
(2023)
André Susano Pinto
,
Alexander Kolesnikov
,
Yuge Shi
,
Lucas Beyer
,
Xiaohua Zhai
Tuning Computer Vision Models With Task Rewards.
ICML
(2023)
Yuge Shi
,
Imant Daunhawer
,
Julia E. Vogt
,
Philip H. S. Torr
,
Amartya Sanyal
How robust are pre-trained models to distribution shift?
CoRR
(2022)
Yuge Shi
,
N. Siddharth
,
Philip H. S. Torr
,
Adam R. Kosiorek
Adversarial Masking for Self-Supervised Learning.
ICML
(2022)
Yuge Shi
,
Jeffrey Seely
,
Philip H. S. Torr
,
Siddharth Narayanaswamy
,
Awni Y. Hannun
,
Nicolas Usunier
,
Gabriel Synnaeve
Gradient Matching for Domain Generalization.
ICLR
(2022)
Yuge Shi
,
N. Siddharth
,
Philip H. S. Torr
,
Adam R. Kosiorek
Adversarial Masking for Self-Supervised Learning.
CoRR
(2022)
Tom Joy
,
Yuge Shi
,
Philip H. S. Torr
,
Tom Rainforth
,
Sebastian M. Schmon
,
Siddharth Narayanaswamy
Learning Multimodal VAEs through Mutual Supervision.
ICLR
(2022)
Yuge Shi
,
Brooks Paige
,
Philip H. S. Torr
,
N. Siddharth
Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models.
ICLR
(2021)
Yuge Shi
,
Jeffrey Seely
,
Philip H. S. Torr
,
N. Siddharth
,
Awni Hannun
,
Nicolas Usunier
,
Gabriel Synnaeve
Gradient Matching for Domain Generalization.
CoRR
(2021)
Tom Joy
,
Yuge Shi
,
Philip H. S. Torr
,
Tom Rainforth
,
Sebastian M. Schmon
,
N. Siddharth
Learning Multimodal VAEs through Mutual Supervision.
CoRR
(2021)
Yuge Shi
,
Brooks Paige
,
Philip H. S. Torr
,
N. Siddharth
Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models.
CoRR
(2020)
Yuge Shi
,
N. Siddharth
,
Brooks Paige
,
Philip H. S. Torr
Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models.
CoRR
(2019)
Yuge Shi
,
Siddharth Narayanaswamy
,
Brooks Paige
,
Philip H. S. Torr
Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models.
NeurIPS
(2019)
Yuge Shi
,
Basura Fernando
,
Richard I. Hartley
Action Anticipation with RBF Kernelized Feature Mapping RNN.
CoRR
(2019)
Yuge Shi
,
Basura Fernando
,
Richard Hartley
Action Anticipation with RBF Kernelized Feature Mapping RNN.
ECCV (10)
(2018)