Results 191 to 200 of about 1,798,077 (286)

Global temperature anomaly prediction by using additive twin LSTM networks. [PDF]

Sci Rep
Keles C, Baran B, Alagoz BB.
europepmc   +1 more source

MGDP: Mastering a Generalized Depth Perception Model for Quadruped Locomotion

Advanced Science, EarlyView.
ABSTRACT Perception‐based Deep Reinforcement Learning (DRL) controllers demonstrate impressive performance on challenging terrains. However, existing controllers still face core limitations, struggling to achieve both terrain generality and platform transferability, and are constrained by high computational overhead and sensitivity to sensor noise.
Yinzhao Dong, Ji Ma, Yidan Lu, Jiahui Zhang, Wanyue Li, Yeke Chen, Teng Zhang, Xuechao Chen, Zhangguo Yu, Peng Lu   +9 more
wiley   +1 more source

Bio-Inspired Neural Network Dynamics-Aware Reinforcement Learning for Spiking Neural Network. [PDF]

Biomimetics (Basel)
Zheng Y, Xue J, Yang J, Zhang Y.
europepmc   +1 more source

High‐Throughput Data Generation and Transfer Learning Enabled Microstructure‐Property Integrated Design of Nickel‐Based Powder Metallurgy Superalloy

Advanced Science, EarlyView.
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li, Hongtao Zhang, Zichao Peng, Yuheng Zhang, Qian Lv, Yihuan Cao, Xuqing Wang, Huadong Fu, Jianxin Xie   +8 more
wiley   +1 more source

Visualising backward information propagation in deep reinforcement learning from a variational data assimilation perspective. [PDF]

Sci Rep
Wang KY.
europepmc   +1 more source

Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks

Advanced Science, EarlyView.
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu, Longfei Lv, Fan Zhang, Si Zhou, Weiwei Gao, Jijun Zhao   +5 more
wiley   +1 more source

PAIR: Reconstructing Single‐Cell Open‐Chromatin Landscapes for Transcription Factor Regulome Mapping

Advanced Science, EarlyView.
scATAC‐seq analysis is often constrained by limited sequencing depth, extreme sparsity, and pervasive technical missingness. PAIR is a probabilistic framework that restores scATAC‐seq accessibility profiles by directly modeling the native cell–peak bipartite structure of chromatin accessibility.
Yanchi Su, Qi Qi, Yi Fan, Yubo Wang, Gaoyang Hao, Ka‐Chun Wong, Yunhe Wang, Xiangtao Li   +7 more
wiley   +1 more source

Author Correction: Foundation model of neural activity predicts response to new stimulus types. [PDF]

Nature
Wang EY, Fahey PG, Ding Z, Papadopoulos S, Ponder K, Weis MA, Chang A, Muhammad T, Patel S, Ding Z, Tran D, Fu J, Schneider-Mizell CM, MICrONS Consortium, Reid RC, Collman F, da Costa NM, Franke K, Ecker AS, Reimer J, Pitkow X, Sinz FH, Tolias AS.   +22 more
europepmc   +1 more source

Harnessing Phase Separation for the Development of High‐Performance Hydrogels

Advanced Science, EarlyView.
ABSTRACT Hydrogels are indispensable for the development of next‐generation bioelectronics, soft robotics, and biomedical devices, where their mechanical properties determine performance and reliability. Among strategies to enhance hydrogel mechanics, phase separation enables controlled heterogeneity resulting in gel networks that are reinforced by ...
Yue Shao, Yiming Ma, Baihao Shao, Molly M. Stevens   +3 more
wiley   +1 more source

Identification and quantification of irreversibility in stochastic systems.

Phys Chem Chem Phys
Ghosal A, Bisker G.
europepmc   +1 more source