Summary of Training Safe Neural Networks with Global Sdp Bounds, by Roman Soletskyi and David “davidad” Dalrymple
Training Safe Neural Networks with Global SDP Boundsby Roman Soletskyi, David “davidad” DalrympleFirst submitted to…
Training Safe Neural Networks with Global SDP Boundsby Roman Soletskyi, David “davidad” DalrympleFirst submitted to…
Analysis of Centrifugal Clutches in Two-Speed Automatic Transmissions with Deep Learning-Based Engagement Predictionby Bo-Yi Lin,…
Learning Rate Optimization for Deep Neural Networks Using Lipschitz Banditsby Padma Priyanka, Sheetal Kalyani, Avhishek…
Deep Fast Machine Learning Utils: A Python Library for Streamlined Machine Learning Prototypingby Fabi PrezjaFirst…
Understanding Simplicity Bias towards Compositional Mappings via Learning Dynamicsby Yi Ren, Danica J. SutherlandFirst submitted…
Robust Training of Neural Networks at Arbitrary Precision and Sparsityby Chengxi Ye, Grace Chu, Yanfeng…
INN-PAR: Invertible Neural Network for PPG to ABP Reconstructionby Soumitra Kundu, Gargi Panda, Saumik Bhattacharya,…
Recent Trends in Modelling the Continuous Time Series using Deep Learning: A Surveyby Mansura Habiba,…
Neural Message Passing Induced by Energy-Constrained Diffusionby Qitian Wu, David Wipf, Junchi YanFirst submitted to…
Optimization and Generalization Guarantees for Weight Normalizationby Pedro Cisneros-Velarde, Zhijie Chen, Sanmi Koyejo, Arindam BanerjeeFirst…