Summary of Learning Generalized Hamiltonians Using Fully Symplectic Mappings, by Harsh Choudhary et al.
Learning Generalized Hamiltonians using fully Symplectic Mappingsby Harsh Choudhary, Chandan Gupta, Vyacheslav kungrutsev, Melvin Leok,…
Summary of Hedging Is Not All You Need: a Simple Baseline For Online Learning Under Haphazard Inputs, by Himanshu Buckchash et al.
Hedging Is Not All You Need: A Simple Baseline for Online Learning Under Haphazard Inputsby…
Summary of Revising the Structure Of Recurrent Neural Networks to Eliminate Numerical Derivatives in Forming Physics Informed Loss Terms with Respect to Time, by Mahyar Jahani-nasab et al.
Revising the Structure of Recurrent Neural Networks to Eliminate Numerical Derivatives in Forming Physics Informed…
Summary of Learning Joint Models Of Prediction and Optimization, by James Kotary et al.
Learning Joint Models of Prediction and Optimizationby James Kotary, Vincenzo Di Vito, Jacob Cristopher, Pascal…
Summary of Unsupervised Adaptive Normalization, by Bilal Faye et al.
Unsupervised Adaptive Normalizationby Bilal Faye, Hanane Azzag, Mustapha Lebbah, Fangchen FangFirst submitted to arxiv on:…
Summary of Rethinking Deep Learning: Propagating Information in Neural Networks Without Backpropagation and Statistical Optimization, by Kei Itoh
Rethinking Deep Learning: Propagating Information in Neural Networks without Backpropagation and Statistical Optimizationby Kei ItohFirst…
Summary of Gradient-free Variational Learning with Conditional Mixture Networks, by Conor Heins et al.
Gradient-free variational learning with conditional mixture networksby Conor Heins, Hao Wu, Dimitrije Markovic, Alexander Tschantz,…
Summary of Artificial Neural Network and Deep Learning: Fundamentals and Theory, by M. M. Hammad
Artificial Neural Network and Deep Learning: Fundamentals and Theoryby M. M. HammadFirst submitted to arxiv…
Summary of Only Strict Saddles in the Energy Landscape Of Predictive Coding Networks?, by Francesco Innocenti et al.
Only Strict Saddles in the Energy Landscape of Predictive Coding Networks?by Francesco Innocenti, El Mehdi…
Summary of Second-order Forward-mode Automatic Differentiation For Optimization, by Adam D. Cobb et al.
Second-Order Forward-Mode Automatic Differentiation for Optimizationby Adam D. Cobb, Atılım Güneş Baydin, Barak A. Pearlmutter,…