Model-Free Real-Time Autonomous Energy Management for a Residential Multi-Carrier Energy System: A Deep Reinforcement Learning Approach. - Yujian Ye; Dawei Qiu; Jonathan Ward; Marcin Abram (IJCAI, 2020)

Democratising blockchain: A minimal agency consensus model. - Marcin Abram; David Galindo; Daniel Honerkamp; Jonathan Ward; Jin-Mann Wong (CoRR, 2020)

Emulating Quantum Dynamics with Neural Networks via Knowledge Distillation. - Yu Yao; Chao Cao; Stephan Haas; Mahak Agarwal; Divyam Khanna; Marcin Abram (CoRR, 2022)

Inferring topological transitions in pattern-forming processes with self-supervised learning. - Marcin Abram; Keith Burghardt; Greg Ver Steeg; Aram Galstyan; Rémi Dingreville (CoRR, 2022)

Performance Weighting for Robust Federated Learning Against Corrupted Sources. - Dimitris Stripelis; Marcin Abram; José Luis Ambite (CoRR, 2022)

Context Matters: Data-Efficient Augmentation of Large Language Models for Scientific Applications. - Xiang Li; Haoran Tang; Siyu Chen; Ziwei Wang; Anurag Maravi; Marcin Abram (CoRR, 2023)

Why does in-context learning fail sometimes? Evaluating in-context learning on open and closed questions. - Xiang Li; Haoran Tang; Siyu Chen; Ziwei Wang; Ryan Chen; Marcin Abram (CoRR, 2024)