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Sébastien M. R. Arnold
Sébastien M. R. Arnold
E-mailová adresa ověřena na: google.com - Domovská stránka
Název
Citace
Citace
Rok
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ...
arXiv preprint arXiv:2312.11805, 2023
11182023
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ...
arXiv preprint arXiv:2403.05530, 2024
1882024
learn2learn: A library for meta-learning research
SMR Arnold, P Mahajan, D Datta, I Bunner, KS Zarkias
arXiv preprint arXiv:2008.12284, 2020
792020
When maml can adapt fast and how to assist when it cannot
S Arnold, S Iqbal, F Sha
International conference on artificial intelligence and statistics, 244-252, 2021
282021
Reducing the variance in online optimization by transporting past gradients
S Arnold, PA Manzagol, R Babanezhad Harikandeh, I Mitliagkas, ...
Advances in Neural Information Processing Systems 32, 2019
232019
Roboclip: One demonstration is enough to learn robot policies
S Sontakke, J Zhang, S Arnold, K Pertsch, E Bıyık, D Sadigh, C Finn, L Itti
Advances in Neural Information Processing Systems 36, 2024
202024
A domain-agnostic approach for characterization of lifelong learning systems
MM Baker, A New, M Aguilar-Simon, Z Al-Halah, SMR Arnold, ...
Neural Networks 160, 274-296, 2023
202023
Uniform sampling over episode difficulty
S Arnold, G Dhillon, A Ravichandran, S Soatto
Advances in Neural Information Processing Systems 34, 1481-1493, 2021
92021
learn2learn, 2019
SM Arnold, P Mahajan, D Datta, I Bunner
8
Can an LLM-powered socially assistive robot effectively and safely deliver cognitive behavioral therapy? A study with university students
MJ Kian, M Zong, K Fischer, A Singh, AM Velentza, P Sang, S Upadhyay, ...
arXiv preprint arXiv:2402.17937, 2024
62024
Policy learning and evaluation with randomized quasi-Monte Carlo
SMR Arnold, P L'Ecuyer, L Chen, Y Chen, F Sha
arXiv preprint arXiv:2202.07808, 2022
62022
Embedding adaptation is still needed for few-shot learning
SMR Arnold, F Sha
arXiv preprint arXiv:2104.07255, 2021
6*2021
Analyzing the variance of policy gradient estimators for the linear-quadratic regulator
JA Preiss, SMR Arnold, CY Wei, M Kloft
arXiv preprint arXiv:1910.01249, 2019
62019
Decoupling adaptation from modeling with meta-optimizers for meta learning
SMR Arnold, S Iqbal, F Sha
5*2019
Writing distributed applications with PyTorch
S Arnold
32017
An Introduction to Distributed Deep Learning
S Arnold
22016
Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More?
J Lee, A Chen, Z Dai, D Dua, DS Sachan, M Boratko, Y Luan, SMR Arnold, ...
arXiv preprint arXiv:2406.13121, 2024
2024
Policy-Induced Self-Supervision Improves Representation Finetuning in Visual RL
SMR Arnold, F Sha
arXiv preprint arXiv:2302.06009, 2023
2023
Accelerating SGD for Distributed Deep-Learning Using Approximated Hessian Matrix
SMR Arnold, C Wang
arXiv preprint arXiv:1709.05069, 2017
2017
Shapechanger: Environments for Transfer Learning
SMR Arnold, TK Pun, TTJ Denisart, FJ Valero-Cuevas
arXiv preprint arXiv:1709.05070, 2017
2017
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Články 1–20