PhysNet: A Neural Network for Predicting Energies, Forces, Dipole Moments, and Partial Charges.
暂无分享,去创建一个
[1] Simon Haykin,et al. Neural Networks and Learning Machines , 2010 .
[2] Sanjiv Kumar,et al. On the Convergence of Adam and Beyond , 2018 .
[3] R. Fletcher. Practical Methods of Optimization , 1988 .
[4] Yoshua Bengio,et al. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.
[5] Grgoire Montavon,et al. Neural Networks: Tricks of the Trade , 2012, Lecture Notes in Computer Science.
[6] Sebastian Thrun,et al. Is Learning The n-th Thing Any Easier Than Learning The First? , 1995, NIPS.
[7] Yoshua Bengio,et al. Pattern Recognition and Neural Networks , 1995 .
[8] Heekuck Oh,et al. Neural Networks for Pattern Recognition , 1993, Adv. Comput..
[9] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[10] Klaus-Robert Müller,et al. SchNet: A continuous-filter convolutional neural network for modeling quantum interactions , 2017, NIPS.
[11] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[12] Klaus-Robert Müller,et al. Quantum-chemical insights from interpretable atomistic neural networks , 2018, Explainable AI.
[13] David S. Ebert,et al. Texturing and Modeling: A Procedural Approach , 1994 .
[14] Ohad Shamir,et al. The Power of Depth for Feedforward Neural Networks , 2015, COLT.
[15] K. Müller,et al. Towards exact molecular dynamics simulations with machine-learned force fields , 2018, Nature Communications.
[16] Jian Sun,et al. Identity Mappings in Deep Residual Networks , 2016, ECCV.
[17] Alex Graves,et al. Recurrent Models of Visual Attention , 2014, NIPS.
[18] David S. Ebert,et al. Texturing & modeling : a procedural approach : 日本語版 , 2009 .
[19] O. Anatole von Lilienfeld,et al. The "DNA" of chemistry: Scalable quantum machine learning with "amons" , 2017, 1707.04146.
[20] Yoshua Bengio,et al. Understanding the difficulty of training deep feedforward neural networks , 2010, AISTATS.
[21] Samuel S. Schoenholz,et al. Neural Message Passing for Quantum Chemistry , 2017, ICML.