PyTorch Time-Series Forecasting: Concepts and Implementation
Technical reference for LSTM-based stock price prediction. Covers data normalization, tensor shapes, training loops, and PyTorch mechanics for recurrent neural networks.
Working notes, surveys, and investigations into particle physics and related mathematics.
Technical reference for LSTM-based stock price prediction. Covers data normalization, tensor shapes, training loops, and PyTorch mechanics for recurrent neural networks.
Notes synthesizing recent developments in dynamical black hole thermodynamics. Classical formulations using event horizons fail for rapidly evolving black holes. Quasi-local horizons and the generalized first law provide a framework for understanding entropy production in realistic scenarios.
Notes on arXiv:2304.01175 examining the connection between quantum 'magic' (non-stabilizerness) and entanglement spectrum dynamics. How measuring the flatness of entanglement spectra under Clifford evolution reveals the presence of non-Clifford resources.
Working through Feynman's path integral formulation and grappling with why classical mechanics emerges as a limiting case of quantum mechanics. Applications to black hole dynamics.
My attempt to map the full particle zoo and understand where the cracks in our best theory actually are. Motivated by Feynman's QED and several arXiv survey papers.