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2020 – today
- 2024
[c11]Edward Hughes, Michael D. Dennis, Jack Parker-Holder, Feryal M. P. Behbahani, Aditi Mavalankar, Yuge Shi, Tom Schaul, Tim Rocktäschel:
Position: Open-Endedness is Essential for Artificial Superhuman Intelligence. ICML 2024- [c10]Ivana Balazevic, Yuge Shi, Pinelopi Papalampidi, Rahma Chaabouni, Skanda Koppula, Olivier J. Hénaff:
Memory Consolidation Enables Long-Context Video Understanding. ICML 2024 - [c9]Jake Bruce, Michael D. Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, Yusuf Aytar, Sarah Bechtle, Feryal M. P. Behbahani, Stephanie C. Y. Chan, Nicolas Heess, Lucy Gonzalez, Simon Osindero, Sherjil Ozair, Scott E. Reed, Jingwei Zhang, Konrad Zolna, Jeff Clune, Nando de Freitas, Satinder Singh, Tim Rocktäschel:
Genie: Generative Interactive Environments. ICML 2024 - [i11]Ivana Balazevic, Yuge Shi, Pinelopi Papalampidi, Rahma Chaabouni, Skanda Koppula, Olivier J. Hénaff:
Memory Consolidation Enables Long-Context Video Understanding. CoRR abs/2402.05861 (2024) - [i10]Jake Bruce, Michael Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, Yusuf Aytar, Sarah Bechtle, Feryal M. P. Behbahani, Stephanie Chan, Nicolas Heess, Lucy Gonzalez, Simon Osindero, Sherjil Ozair, Scott E. Reed, Jingwei Zhang, Konrad Zolna, Jeff Clune, Nando de Freitas, Satinder Singh, Tim Rocktäschel:
Genie: Generative Interactive Environments. CoRR abs/2402.15391 (2024) - [i9]Edward Hughes, Michael Dennis, Jack Parker-Holder, Feryal M. P. Behbahani, Aditi Mavalankar, Yuge Shi, Tom Schaul, Tim Rocktäschel:
Open-Endedness is Essential for Artificial Superhuman Intelligence. CoRR abs/2406.04268 (2024) - 2023
- [c8]Yuge Shi, Imant Daunhawer, Julia E. Vogt, Philip H. S. Torr, Amartya Sanyal:
How robust is unsupervised representation learning to distribution shift? ICLR 2023 - [c7]André Susano Pinto, Alexander Kolesnikov, Yuge Shi, Lucas Beyer, Xiaohua Zhai:
Tuning Computer Vision Models With Task Rewards. ICML 2023: 33229-33239 - [i8]André Susano Pinto, Alexander Kolesnikov, Yuge Shi, Lucas Beyer, Xiaohua Zhai:
Tuning computer vision models with task rewards. CoRR abs/2302.08242 (2023) - 2022
- [c6]Tom Joy, Yuge Shi, Philip H. S. Torr, Tom Rainforth, Sebastian M. Schmon, Siddharth Narayanaswamy:
Learning Multimodal VAEs through Mutual Supervision. ICLR 2022 - [c5]Yuge Shi, Jeffrey Seely, Philip H. S. Torr, Siddharth Narayanaswamy, Awni Y. Hannun, Nicolas Usunier, Gabriel Synnaeve:
Gradient Matching for Domain Generalization. ICLR 2022 - [c4]Yuge Shi, N. Siddharth, Philip H. S. Torr, Adam R. Kosiorek:
Adversarial Masking for Self-Supervised Learning. ICML 2022: 20026-20040 - [i7]Yuge Shi, N. Siddharth, Philip H. S. Torr, Adam R. Kosiorek:
Adversarial Masking for Self-Supervised Learning. CoRR abs/2201.13100 (2022) - [i6]Yuge Shi, Imant Daunhawer, Julia E. Vogt
, Philip H. S. Torr, Amartya Sanyal:
How robust are pre-trained models to distribution shift? CoRR abs/2206.08871 (2022) - 2021
- [c3]Yuge Shi, Brooks Paige, Philip H. S. Torr, N. Siddharth:
Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models. ICLR 2021 - [i5]Yuge Shi, Jeffrey Seely, Philip H. S. Torr, N. Siddharth, Awni Y. Hannun, Nicolas Usunier, Gabriel Synnaeve:
Gradient Matching for Domain Generalization. CoRR abs/2104.09937 (2021) - [i4]Tom Joy, Yuge Shi, Philip H. S. Torr, Tom Rainforth, Sebastian M. Schmon, N. Siddharth:
Learning Multimodal VAEs through Mutual Supervision. CoRR abs/2106.12570 (2021) - 2020
- [i3]Yuge Shi, Brooks Paige, Philip H. S. Torr, N. Siddharth:
Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models. CoRR abs/2007.01179 (2020)
2010 – 2019
- 2019
- [c2]Yuge Shi, Siddharth Narayanaswamy, Brooks Paige, Philip H. S. Torr:
Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models. NeurIPS 2019: 15692-15703 - [i2]Yuge Shi, N. Siddharth, Brooks Paige, Philip H. S. Torr:
Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models. CoRR abs/1911.03393 (2019) - [i1]Yuge Shi, Basura Fernando, Richard I. Hartley:
Action Anticipation with RBF Kernelized Feature Mapping RNN. CoRR abs/1911.07806 (2019) - 2018
- [c1]Yuge Shi, Basura Fernando, Richard Hartley:
Action Anticipation with RBF Kernelized Feature Mapping RNN. ECCV (10) 2018: 305-322
Coauthor Index
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