Talks Some recent talks “Physical” laws of deep learning A statistical framework of watermarks for large language models Improving peer review for ML/AI conferences Gaussian differential privacy with applications to the US Census Old talks A phenomenological approach toward understanding deep learning Analyzing optimization methods via differential equations SLOPE: A method for FDR control in high dimensions
