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Ziming Liu
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Scientific discovery in the age of artificial intelligence
H Wang, T Fu, Y Du, W Gao, K Huang, Z Liu, P Chandak, S Liu, ...
Nature 620 (7972), 47-60, 2023
1108*2023
KAN: Kolmogorov-Arnold Networks
Z Liu, Y Wang, S Vaidya, F Ruehle, J Halverson, M Soljačić, TY Hou, ...
arXiv:2404.19756, 2024
844*2024
Machine learning conservation laws from trajectories
Z Liu, M Tegmark
Physical Review Letters 126 (18), 180604, 2021
1672021
Towards understanding grokking: An effective theory of representation learning
Z Liu, O Kitouni, NS Nolte, E Michaud, M Tegmark, M Williams
Advances in Neural Information Processing Systems 35, 34651-34663, 2022
1542022
Omnigrok: Grokking Beyond Algorithmic Data
Z Liu, E Michaud, M Tegmark
Eleventh International Conference on Learning Representations, 2023
1042023
Poisson flow generative models
Y Xu*, Z Liu*, M Tegmark, T Jaakkola
Advances in Neural Information Processing Systems 35, 16782-16795, 2022
952022
The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks
Z Zhong*, Z Liu*, M Tegmark, J Andreas
Thirty-seventh Conference on Neural Information Processing Systems, 2023
802023
The quantization model of neural scaling
E Michaud, Z Liu, G Uzay, M Tegmark
Advances in Neural Information Processing Systems, 2023
762023
Machine learning hidden symmetries
Z Liu, M Tegmark
Physical Review Letters 128 (18), 180201, 2022
712022
PFGM++: Unlocking the Potential of Physics-Inspired Generative Models
Y Xu, Z Liu, Y Tian, T Shangyuan, M Tegmark, T Jaakkola
Fortieth International Conference on Machine Learning, 2023
612023
KAN 2.0: Kolmogorov-Arnold Networks Meet Science
Z Liu, P Ma, Y Wang, W Matusik, M Tegmark
arXiv: 2408.10205, 2024
562024
Restart Sampling for Improving Generative Processes
Y Xu, M Deng, X Cheng, Y Tian, Z Liu, T Jaakkola
arXiv: 2306.14878, 2023
542023
Machine learning conservation laws from differential equations
Z Liu, V Madhavan, M Tegmark
Physical Review E 106 (4), 045307, 2022
482022
Seeing is believing: Brain-inspired modular training for mechanistic interpretability
Z Liu, E Gan, M Tegmark
Entropy 26 (1), 41, 2023
452023
Precision machine learning
EJ Michaud, Z Liu, M Tegmark
Entropy 25 (1), 175, 2023
422023
Applications of deep learning to relativistic hydrodynamics
H Huang, B Xiao, Z Liu, Z Wu, Y Mu, H Song
Physical Review Research 3 (2), 023256, 2021
342021
Principal component analysis of collective flow in relativistic heavy-ion collisions
Z Liu, W Zhao, H Song
The European Physical Journal C 79 (10), 870, 2019
312019
Machine-learning nonconservative dynamics for new-physics detection
Z Liu, B Wang, Q Meng, W Chen, M Tegmark, TY Liu
Physical Review E 104 (5), 055302, 2021
302021
Physics-augmented learning: A new paradigm beyond physics-informed learning
Z Liu, Y Chen, Y Du, M Tegmark
arXiv preprint arXiv:2109.13901, 2021
272021
Interpretable conservation laws as sparse invariants
Z Liu, PO Sturm, S Bharadwaj, SJ Silva, M Tegmark
Physical Review E 109 (2), L023301, 2024
14*2024
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