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2020 – today
- 2024
[i6]Xiang Li, Haoran Tang, Siyu Chen, Ziwei Wang, Ryan Chen, Marcin Abram:
Why does in-context learning fail sometimes? Evaluating in-context learning on open and closed questions. CoRR abs/2407.02028 (2024)- 2023
- [i5]Xiang Li, Haoran Tang, Siyu Chen, Ziwei Wang, Anurag Maravi, Marcin Abram
:
Context Matters: Data-Efficient Augmentation of Large Language Models for Scientific Applications. CoRR abs/2312.07069 (2023) - 2022
- [i4]Yu Yao, Chao Cao, Stephan Haas, Mahak Agarwal, Divyam Khanna, Marcin Abram:
Emulating Quantum Dynamics with Neural Networks via Knowledge Distillation. CoRR abs/2203.10200 (2022) - [i3]Marcin Abram, Keith Burghardt, Greg Ver Steeg, Aram Galstyan, Rémi Dingreville:
Inferring topological transitions in pattern-forming processes with self-supervised learning. CoRR abs/2203.10204 (2022) - [i2]Dimitris Stripelis, Marcin Abram, José Luis Ambite:
Performance Weighting for Robust Federated Learning Against Corrupted Sources. CoRR abs/2205.01184 (2022) - 2020
- [c1]Yujian Ye, Dawei Qiu, Jonathan Ward, Marcin Abram:
Model-Free Real-Time Autonomous Energy Management for a Residential Multi-Carrier Energy System: A Deep Reinforcement Learning Approach. IJCAI 2020: 339-346 - [i1]Marcin Abram, David Galindo, Daniel Honerkamp, Jonathan Ward, Jin-Mann Wong:
Democratising blockchain: A minimal agency consensus model. CoRR abs/2006.05390 (2020)
Coauthor Index
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