87 citations · 221 across the 37 of their papers we have counts for
6 papers · 1 filter
Learning Lévy density via adaptive RKHS regression with bi-level optimization
Luxuan Yang, Fei Lu, Ting Gao +2
We propose a nonparametric method to learn the Lévy density from probability density data governed by a nonlocal Fokker-Planck equation. We recast the problem as identifying the ke…
Artificial intelligence as a surrogate brain: Bridging neural dynamical models and data
Yinuo Zhang, Demao Liu, Zhichao Liang +6
Recent breakthroughs in artificial intelligence (AI) are reshaping the way we construct computational counterparts of the brain, giving rise to a new class of ``surrogate brains''.…
Latent Iterative Refinement Flow: A Geometric Constrained Approach for Few-Shot Generation
Songtao Li, Tianqi Hou, Zhenyu Liao +1
Diffusion and flow-matching models trained with limited data often tend to memorize the training data instead of generalization, leading to severely reduced diversity. In this pape…
NeuronSeek: On Stability and Expressivity of Task-driven Neurons
Hanyu Pei, Jing-Xiao Liao, Qibin Zhao +4
Drawing inspiration from our human brain that designs different neurons for different tasks, recent advances in deep learning have explored modifying a network's neurons to develop…
Adaptive control for multi-scale stochastic dynamical systems with stochastic next generation reservoir computing
Jiani Cheng, Ting Gao, Jinqiao Duan
The rapid advancement of neuroscience and machine learning has established data-driven stochastic dynamical system modeling as a powerful tool for understanding and controlling hig…
Hedging with Sparse Reward Reinforcement Learning
Yiheng Ding, Gangnan Yuan, Dewei Zuo +1
Derivatives, as a critical class of financial instruments, isolate and trade the price attributes of risk assets such as stocks, commodities, and indices, aiding risk management an…