Video

Self-Supervised Learning

Bolei Zhou – From Network Dissection to Policy Dissection: Emergent Concepts in Deep Representations

February 20, 2024

Video

Self-Supervised Learning

Xiao Fu – Multiview and Self-Supervised Representation Learning: Nonlinear Mixture Identification

February 20, 2024

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Self-Supervised Learning

Frederick Klauschen – AI in cancer research and diagnostics – IPAM at UCLA

February 20, 2024

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Self-Supervised Learning

Osbert Bastani – Interpretable Machine Learning via Program Synthesis – IPAM at UCLA

February 20, 2024

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Self-Supervised Learning

Klaus Robert Muller – AI for the Sciences: Recent Developments for XAI – IPAM at UCLA

February 20, 2024

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Self-Supervised Learning

Jaesik Choi – Explainable AI to Analyze Internal Decision Mechanism of Deep Neural Networks

February 20, 2024

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Self-Supervised Learning

Bin Yu – Interpreting Deep Neural Networks towards Trustworthiness – IPAM at UCLA

February 20, 2024

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Self-Supervised Learning

Evrim Acar – Constrained Multimodal Data Mining using Coupled Matrix and Tensor Factorizations

February 20, 2024

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Self-Supervised Learning

Wojciech Samek – Concept-Level Explainable AI – IPAM at UCLA

February 20, 2024

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Self-Supervised Learning

Cecelia Clementi – Designing molecular models with machine learning and experimental data

February 20, 2024

Category - AI Science

Computer Vision Deep Learning Markov Models Neural Network Quantum Computing in AI Reinforcement Learning Self-Supervised Learning Support Vector Machines (SVM)Transformer Architecture

Transformer Architecture

How to check if a neural network has learned a specific phenomenon?

AI Science, Natural Language Processing (NLP)

Training an AI to create poetry (NLP Zero to Hero – Part 6)

AI Science, Natural Language Processing (NLP)

Long Short-Term Memory for NLP (NLP Zero to Hero – Part 5)

AI Science, Natural Language Processing (NLP)

ML with Recurrent Neural Networks (NLP Zero to Hero – Part 4)

AI Science, Natural Language Processing (NLP)

Training a model to recognize sentiment in text (NLP Zero to Hero – Part 3)

AI Science, Natural Language Processing (NLP)

Sequencing – Turning sentences into data (NLP Zero to Hero – Part 2)

AI Science, Natural Language Processing (NLP)

Natural Language Processing – Tokenization (NLP Zero to Hero – Part 1)

Reinforcement Learning, Reinforcement Learning CS234, Standford U, Standford University

Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 16 – Monte Carlo Tree Search

Reinforcement Learning, Reinforcement Learning CS234, Standford U, Standford University

Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 15 – Batch Reinforcement Learning

Reinforcement Learning, Reinforcement Learning CS234, Standford U, Standford University

Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 13 – Fast Reinforcement Learning III

Reinforcement Learning, Reinforcement Learning CS234, Standford U, Standford University

Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 12 – Fast Reinforcement Learning II

Reinforcement Learning, Reinforcement Learning CS234, Standford U, Standford University

Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 11 – Fast Reinforcement Learning