Mathematics and Machine Creativity: A Survey on Bridging Mathematics with AI
S Liang, W Zhang, T Zhong - arXiv preprint arXiv:2412.16543, 2024 - arxiv.org
This paper presents a comprehensive survey on the applications of artificial intelligence (AI)
in mathematical research, highlighting the transformative role AI has begun to play in this …
in mathematical research, highlighting the transformative role AI has begun to play in this …
Meta-Designing Quantum Experiments with Language Models
Artificial Intelligence (AI) has the potential to significantly advance scientific discovery by
finding solutions beyond human capabilities. However, these super-human solutions are …
finding solutions beyond human capabilities. However, these super-human solutions are …
Learning Interpretable Network Dynamics via Universal Neural Symbolic Regression
J Hu, J Cui, B Yang - arXiv preprint arXiv:2411.06833, 2024 - arxiv.org
Discovering governing equations of complex network dynamics is a fundamental challenge
in contemporary science with rich data, which can uncover the mysterious patterns and …
in contemporary science with rich data, which can uncover the mysterious patterns and …
Formal Mathematical Reasoning: A New Frontier in AI
AI for Mathematics (AI4Math) is not only intriguing intellectually but also crucial for AI-driven
discovery in science, engineering, and beyond. Extensive efforts on AI4Math have mirrored …
discovery in science, engineering, and beyond. Extensive efforts on AI4Math have mirrored …
ViSymRe: Vision-guided Multimodal Symbolic Regression
D Li, J Yin, J Xu, X Li, J Zhang - arXiv preprint arXiv:2412.11139, 2024 - arxiv.org
Symbolic regression automatically searches for mathematical equations to reveal underlying
mechanisms within datasets, offering enhanced interpretability compared to black box …
mechanisms within datasets, offering enhanced interpretability compared to black box …
AIGS: Generating Science from AI-Powered Automated Falsification
Rapid development of artificial intelligence has drastically accelerated the development of
scientific discovery. Trained with large-scale observation data, deep neural networks extract …
scientific discovery. Trained with large-scale observation data, deep neural networks extract …
ABEL: Sample Efficient Online Reinforcement Learning for Neural Theorem Proving
We propose a scalable and efficient reinforcement learning framework as a strong baseline
for theorem proving with limited data. This baseline reaches performances comparable to …
for theorem proving with limited data. This baseline reaches performances comparable to …