| Learning activation functions to improve deep neural networks F Agostinelli, M Hoffman, P Sadowski, P Baldi International Conference on Learning Representations Workshop, 2015 | 716 | 2015 |
| Adaptive multi-column deep neural networks with application to robust image denoising F Agostinelli, MR Anderson, H Lee Advances in neural information processing systems 26, 2013 | 315 | 2013 |
| Solving the Rubik’s cube with deep reinforcement learning and search F Agostinelli, S McAleer, A Shmakov, P Baldi Nature Machine Intelligence 1 (8), 356-363, 2019 | 228 | 2019 |
| What time is it? Deep learning approaches for circadian rhythms F Agostinelli, N Ceglia, B Shahbaba, P Sassone-Corsi, P Baldi Bioinformatics 32 (12), i8-i17, 2016 | 107 | 2016 |
| Solving the rubik's cube with approximate policy iteration S McAleer, F Agostinelli, AK Shmakov, P Baldi International Conference on Learning Representations, 2019 | 98* | 2019 |
| From reinforcement learning to deep reinforcement learning: An overview F Agostinelli, G Hocquet, S Singh, P Baldi Braverman Readings in Machine Learning. Key Ideas from Inception to Current …, 2018 | 70 | 2018 |
| Splash: Learnable activation functions for improving accuracy and adversarial robustness M Tavakoli, F Agostinelli, P Baldi Neural Networks 140, 1-12, 2021 | 47 | 2021 |
| CircadiOmics: circadian omic web portal N Ceglia, Y Liu, S Chen, F Agostinelli, K Eckel-Mahan, P Sassone-Corsi, ... Nucleic acids research 46 (W1), W157-W162, 2018 | 46 | 2018 |
| Hippocampal ensembles represent sequential relationships among an extended sequence of nonspatial events B Shahbaba, L Li, F Agostinelli, M Saraf, KW Cooper, D Haghverdian, ... Nature communications 13 (1), 787, 2022 | 44* | 2022 |
| Q* Search: Heuristic Search with Deep Q-Networks F Agostinelli, SS Shperberg, A Shmakov, S McAleer, R Fox, P Baldi ICAPS Workshop on Bridging the Gap between AI Planning and Reinforcement …, 2024 | 21* | 2024 |
| Designing children’s new learning partner: collaborative artificial intelligence for learning to solve the Rubik’s cube F Agostinelli, M Mavalankar, V Khandelwal, H Tang, D Wu, B Berry, ... Proceedings of the 20th Annual ACM Interaction Design and Children …, 2021 | 12 | 2021 |
| Obtaining approximately admissible heuristic functions through deep reinforcement learning and A* search F Agostinelli, S McAleer, A Shmakov, R Fox, M Valtorta, B Srivastava, ... Bridging the Gap between AI Planning and Reinforcement Learning workshop at …, 2021 | 8 | 2021 |
| CircadiOmics: circadian omic web portal M Samad, F Agostinelli, T Sato, K Shimaji, P Baldi Nucleic acids research 50 (W1), W183-W190, 2022 | 6 | 2022 |
| Specifying goals to deep neural networks with answer set programming F Agostinelli, R Panta, V Khandelwal Proceedings of the International Conference on Automated Planning and …, 2024 | 5 | 2024 |
| Explainable artificial intelligence (XAI) user interface design for solving a Rubik’s Cube C Bradley, D Wu, H Tang, I Singh, K Wydant, B Capps, K Wong, ... International Conference on Human-Computer Interaction, 605-612, 2022 | 5 | 2022 |
| ALLURE: A Multi-Modal Guided Environment for Helping Children Learn to Solve a Rubik’s Cube with Automatic Solving and Interactive Explanations K Lakkaraju, T Hassan, V Khandelwal, P Singh, C Bradley, R Shah, ... AAAI Conference on Artificial Intelligence - Demonstration Track, 2022 | 4 | 2022 |
| On Solving the Rubik's Cube with Domain-Independent Planners Using Standard Representations B Muppasani, V Pallagani, B Srivastava, F Agostinelli arXiv preprint arXiv:2307.13552, 2023 | 3 | 2023 |
| Synthesis of CdZnTeSe single crystals for room temperature radiation detector fabrication: mitigation of hole trapping effects using a convolutional neural network SK Chaudhuri, JW Kleppinger, OF Karadavut, R Nag, R Panta, ... Journal of Materials Science: Materials in Electronics 33 (3), 1452-1463, 2022 | 3 | 2022 |
| Improving survey aggregation with sparsely represented signals T Shi, F Agostinelli, M Staib, D Wipf, T Moscibroda Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge …, 2016 | 3 | 2016 |
| Deep Learning for Puzzles and Circadian Rhythms F Agostinelli University of California, Irvine, 2019 | 2 | 2019 |
Pierre BaldiProfessor, University of California, Irvine在 ics.uci.edu 的电子邮件经过验证
