shashank JaininGoPenAIUnderstanding Physics-Informed Neural Networks (PINNs)Physics-Informed Neural Networks (PINNs) are a class of machine learning models that combine data-driven techniques with physical laws…16h ago16h ago
shashank JaininAI MindPredicting Singular Values with Neural NetworksIntroduction: What Are Singular Values and Why Are They Important?2d ago2d ago
shashank JaininGoPenAILiquid Neural Networks: A Basic Implementation for Time Series ForecastingWhat are Liquid Neural Networks?2d ago2d ago
shashank JainDiscovering the Inner Workings of Language Models: A Deep Dive into “The Remarkable Robustness of…Introduction:Jul 13Jul 13
shashank JainUnderstanding Entropy-SGD: A Way to Train Better AI ModelsToday I try to cover a very interesting paper https://arxiv.org/abs/1611.01838 . The paper talks about usign Entropy within SGD to…Jul 11Jul 11
shashank JaininGoPenAIOptimizing LSTM Autoencoder Latent Dimension using Mutual Information and BOIntroduction:Jul 10Jul 10
shashank JaininGoPenAIResidual Networks Explained: Deep Learning with Residual NetworksIntroductionJun 29Jun 29
shashank JaininGoPenAIUnderstanding Kolmogorov-Arnold Networks (KANs) and Their Application in Variational AutoencodersToday, we’ll be diving into the Kolmogorov-Arnold Networks, or KANs for short. We’re going to explore how KANs can potentially…Jun 28Jun 28
shashank JainUnderstanding Cambrian-1: A Deep Dive into Advanced Visual-Language AIIntroduction:Jun 26Jun 26