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Michael B. Chang
Michael B. Chang
Research Scientist, Google DeepMind
Bestätigte E-Mail-Adresse bei berkeley.edu - Startseite
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Zitiert von
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Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ...
arXiv preprint arXiv:2312.11805, 2023
25132023
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
G Team, P Georgiev, VI Lei, R Burnell, L Bai, A Gulati, G Tanzer, ...
arXiv preprint arXiv:2403.05530, 2024
9902024
A Compositional Object-Based Approach To Learning Physical Dynamics
MB Chang, T Ullman, A Torralba, JB Tenenbaum
International Conference on Learning Representations 5, 2016
5162016
Relational Neural Expectation Maximization: Unsupervised Discovery of Objects and their Interactions
S van Steenkiste, M Chang, K Greff, J Schmidhuber
International Conference on Learning Representations 6, 2018
3212018
Mcp: Learning composable hierarchical control with multiplicative compositional policies
XB Peng, M Chang, G Zhang, P Abbeel, S Levine
Advances in neural information processing systems 32, 2019
2362019
Entity Abstraction in Visual Model-Based Reinforcement Learning
R Veerapaneni*, JD Co-Reyes*, M Chang*, M Janner, C Finn, J Wu, ...
Conference on Robot Learning, 2019
2262019
Doing more with less: Meta-reasoning and meta-learning in humans and machines
TL Griffiths, F Callaway, MB Chang, E Grant, PM Krueger, F Lieder
Current Opinion in Behavioral Sciences 29, 24-30, 2019
1522019
Automatically composing representation transformations as a means for generalization
MB Chang, A Gupta, S Levine, TL Griffiths
International Conference on Learning Representations 7, 2018
872018
Understanding visual concepts with continuation learning
WF Whitney, M Chang, T Kulkarni, JB Tenenbaum
arXiv preprint arXiv:1602.06822, 2016
522016
Object representations as fixed points: Training iterative refinement algorithms with implicit differentiation
M Chang, T Griffiths, S Levine
Advances in Neural Information Processing Systems 35, 32694-32708, 2022
512022
Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions
M Chang, S Kaushik, SM Weinberg, TL Griffiths, S Levine
International Conference on Machine Learning 37, 2020
182020
Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment
M Chang, S Kaushik, S Levine, TL Griffiths
International Conference on Machine Learning 139, 1452-1462, 2021
122021
Representational efficiency outweighs action efficiency in human program induction
S Sanborn, DD Bourgin, M Chang, TL Griffiths
Annual Meeting of the Cognitive Science Society (CogSci), 2018
112018
Explore and control with adversarial surprise
A Fickinger, N Jaques, S Parajuli, M Chang, N Rhinehart, G Berseth, ...
arXiv preprint arXiv:2107.07394, 2021
102021
Neural constraint satisfaction: Hierarchical abstraction for combinatorial generalization in object rearrangement
M Chang, AL Dayan, F Meier, TL Griffiths, S Levine, A Zhang
arXiv preprint arXiv:2303.11373, 2023
42023
Im-promptu: in-context composition from image prompts
B Dedhia, M Chang, J Snell, T Griffiths, N Jha
Advances in Neural Information Processing Systems 36, 2024
22024
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