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Episodes


Stanford CS236: Deep Generative Models I 2023 I Lecture 4 - Maximum Likelihood Learning

Stanford CS236: Deep Generative Models I 2023 I Lecture 3 - Autoregressive Models

Stanford CS236: Deep Generative Models I 2023 I Lecture 2 - Background

Stanford CS236: Deep Generative Models I 2023 I Lecture 1 - Introduction
This podcast episode explores the importance of deep generative models and their applications in various domains. It discusses the challenges of understanding complex objects in computer vision and natural language processing, highlighting the philosophy of generative modeling approaches and the need for a deep underst...

Stanford CS25: V4 I Jason Wei & Hyung Won Chung of OpenAI

Stanford Seminar - Towards trusted human-centric robot autonomy

Information Session: Stanford Graduate Degrees, Certificates, and Courses I 2024

Information Session: Leading People, Culture, and Innovation Program

Stanford CS25: V4 I Overview of Transformers

Stanford Seminar - Towards Safe and Efficient Learning in the Physical World

Stanford EE274: Data Compression I 2023 I Lecture 18 - Video Compression

Stanford EE274: Data Compression I 2023 I Lecture 8 - Beyond IID distributions: Conditional entropy

Stanford EE274: Data Compression I 2023 I Lecture 5 - Asymptotic Equipartition Property

Stanford EE274: Data Compression I 2023 I Lecture 3 - Kraft Inequality, Entropy, Introduction to SCL

Stanford EE274: Data Compression I 2023 I Lecture 11 - Lossy Compression Basics; Quantization

Stanford EE274: Data Compression I 2023 I Lecture 6 - Arithmetic Coding

Stanford EE274: Data Compression I 2023 I Lecture 16 - Learnt Image Compression

Stanford EE274: Data Compression I 2023 I Lecture 1 - Course Intro, Lossless Data Compression Basics

Stanford EE274: Data Compression I 2023 I Lecture 17 - Humans and Compression
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