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2020 – today
- 2024
[i11]Yuejiang Liu, Alexandre Alahi:
Co-Supervised Learning: Improving Weak-to-Strong Generalization with Hierarchical Mixture of Experts. CoRR abs/2402.15505 (2024)- [i10]Jifeng Wang, Kaouther Messaoud, Yuejiang Liu, Juergen Gall, Alexandre Alahi:
Forecast-PEFT: Parameter-Efficient Fine-Tuning for Pre-trained Motion Forecasting Models. CoRR abs/2407.19564 (2024) - [i9]Yuejiang Liu, Jubayer Ibn Hamid, Annie Xie, Yoonho Lee, Maximilian Du, Chelsea Finn:
Bidirectional Decoding: Improving Action Chunking via Closed-Loop Resampling. CoRR abs/2408.17355 (2024) - 2023
- [c11]Yuejiang Liu, Alexandre Alahi, Chris Russell, Max Horn, Dominik Zietlow, Bernhard Schölkopf, Francesco Locatello:
Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning. CLeaR 2023: 553-573 - [c10]Hao Zhao, Yuejiang Liu, Alexandre Alahi, Tao Lin:
On Pitfalls of Test-Time Adaptation. ICML 2023: 42058-42080 - [i8]Yuejiang Liu, Alexandre Alahi, Chris Russell
, Max Horn, Dominik Zietlow, Bernhard Schölkopf, Francesco Locatello:
Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning. CoRR abs/2301.05169 (2023) - [i7]Hao Zhao, Yuejiang Liu, Alexandre Alahi, Tao Lin:
On Pitfalls of Test-Time Adaptation. CoRR abs/2306.03536 (2023) - [i6]Yuejiang Liu, Ahmad Rahimi, Po-Chien Luan, Frano Rajic, Alexandre Alahi:
Sim-to-Real Causal Transfer: A Metric Learning Approach to Causally-Aware Interaction Representations. CoRR abs/2312.04540 (2023) - 2022
- [c9]Parth Kothari, Danya Li, Yuejiang Liu, Alexandre Alahi:
Motion Style Transfer: Modular Low-Rank Adaptation for Deep Motion Forecasting. CoRL 2022: 774-784 - [c8]Yuejiang Liu, Riccardo Cadei, Jonas Schweizer, Sherwin Bahmani, Alexandre Alahi:
Towards Robust and Adaptive Motion Forecasting: A Causal Representation Perspective. CVPR 2022: 17060-17071 - [i5]Parth Kothari, Danya Li, Yuejiang Liu, Alexandre Alahi:
Motion Style Transfer: Modular Low-Rank Adaptation for Deep Motion Forecasting. CoRR abs/2211.03165 (2022) - 2021
- [c7]Yuejiang Liu, Qi Yan, Alexandre Alahi:
Social NCE: Contrastive Learning of Socially-aware Motion Representations. ICCV 2021: 15098-15109 - [c6]Behnam Parsaeifard, Saeed Saadatnejad, Yuejiang Liu, Taylor Mordan, Alexandre Alahi:
Learning Decoupled Representations for Human Pose Forecasting. ICCVW 2021: 2294-2303 - [c5]Yuejiang Liu, Parth Kothari, Bastien van Delft, Baptiste Bellot-Gurlet, Taylor Mordan, Alexandre Alahi:
TTT++: When Does Self-Supervised Test-Time Training Fail or Thrive? NeurIPS 2021: 21808-21820 - [i4]Yuejiang Liu, Riccardo Cadei, Jonas Schweizer, Sherwin Bahmani, Alexandre Alahi:
Towards Robust and Adaptive Motion Forecasting: A Causal Representation Perspective. CoRR abs/2111.14820 (2021) - 2020
- [c4]Yuejiang Liu, Parth Kothari, Alexandre Alahi:
Collaborative Sampling in Generative Adversarial Networks. AAAI 2020: 4948-4956 - [i3]Yuejiang Liu, Qi Yan, Alexandre Alahi:
Social NCE: Contrastive Learning of Socially-aware Motion Representations. CoRR abs/2012.11717 (2020)
2010 – 2019
- 2019
- [c3]Changan Chen, Yuejiang Liu, Sven Kreiss, Alexandre Alahi:
Crowd-Robot Interaction: Crowd-Aware Robot Navigation With Attention-Based Deep Reinforcement Learning. ICRA 2019: 6015-6022 - [i2]Yuejiang Liu, Parth Kothari, Alexandre Alahi:
Collaborative GAN Sampling. CoRR abs/1902.00813 (2019) - 2018
- [c2]Yuejiang Liu, An Xu, Zichong Chen:
Map-based Deep Imitation Learning for Obstacle Avoidance. IROS 2018: 8644-8649 - [i1]Changan Chen, Yuejiang Liu, Sven Kreiss, Alexandre Alahi:
Crowd-Robot Interaction: Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning. CoRR abs/1809.08835 (2018) - 2017
- [c1]Yuejiang Liu, Jean-Hubert Hours, Giorgos Stathopoulos, Colin N. Jones:
Real-time distributed algorithms for nonconvex optimal power flow. ACC 2017: 3380-3385
Coauthor Index
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