17:46

Value of Information and Reward Specification in Active Inference

15:27

Grid Cell Inspired Fragmentation and Recall for Efficient Map Building

22:27

A FALSE SENSE OF PRIVACY IN AI

13:23

A Hopfield Network for Neuromodulatory Arousal State | NeuroAI

10:07

Multimodal Foundation World Models for Generalist Embodied Agents

12:44

Video of Thought - The video version of chain of thought (CoT)

13:42

Next-GPT: Any-to-Any Multimodal LLM

17:59

ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain

37:11

The Secret to Advancing Your AI Career in 2024 (and 2025)

28:20

Building High Throughput Data Management Systems

25:48

Everything about the best LLM on Earth Grok 3 w/ Elon Musk

26:38

GROK 3 in 26 Minutes w/ Elon Musk on X [4K60]

02:39:17

Out-of-Distribution Generalization: Shortcuts, Spuriousness, and Stability

43:29

The Shape of AI to Come! Yann LeCun at AI Summit

31:11

State Space Models (SSMs) and the return of RNNs | ICML

13:33

xLSTM: Extended Long Short Term Memory

45:56

AI Action Summit Firechat w/ Yann LeCun, Schölkopf and Stéphane Mallat

02:31:03

Language Models meet World Models (and Agent Models)

47:17

The Shape of AI to Come! Yann LeCun at AI Action Summit 2025

07:12

Antonio Orvieto: Resurrecting RNN for Long Sequences at ICML 2024

02:14:53

Language Modeling: A Tutorial on Data Preparation, Model Training, and Adaptation

02:29:34

Advancing Data Selection for Foundation Models: From Heuristics to Principled Methods

02:17:49

Beyond Decoding: Meta-Generation Algorithms for Large Language Models | NeurIPS

02:32:17

Watermarking for Large Language Models | Yu-Xiang Wang · Lei Li · Xuandong Zhao

49:08

Albert Gu: Structured State Space Models for Deep Sequence Modeling at NeurIPS

19:25

Muhammad Adnan- Keyformer: KV Cache reduction through key tokens selection

43:11

Naren Srivaths Raman - Reinforcement Learning: Trends, Applications, and Challenges at NeurIPS

01:00:28

Yejin Choi: Possible Impossibilities and Impossible Possibilities | MLSys 2024

30:39

Albert Gu: On the Tradeoffs of State Space Models

02:22:34

Andrew Ng: Application Development using Large Language Models at NeurIPS

16:04

OpenAI - Weak to Strong Generalization: Eliciting Strong Capabilities with Weak Supervision

01:20:53

Jeff Dean (Google Research & Deep Mind): Advances in ML for Systems and Systems for ML | MLSys 2024

09:51

Keming Lu (Alibaba Research) - Qwen: Towards a Generalist Model at NeurIPS | Open Source LLM

01:23:28

Jeff Dean (Google Research & DeepMind): Exciting Directions in ML for Computer Systems

22:30

Greg Corrado, Jeff Dean: Distributed Representations of Words and Phrases & their Compositionality

52:40

Yoshua Bengio et al: What is out of distribution (OOD) generalization & why is it important? NeurIPS

08:07

Q&A for Ilya Sutskever at NeurIPS 2024 (Test of Time Award)

24:37

Ilya Sutskever: Sequence to sequence learning with neural networks | NeurIPS 2024 Test of Time Award

01:24:10

Yoshua Bengio sharing on his Deep Learning Journey

01:24:10

Deep Learning | A Deep Learning Journey | Yoshua Bengio | NeurIPS

53:09

Applied AI | Insights from NVIDIA Research | Bill Dally

23:36

CV | Raytracing for Deep Neural Networks Training

23:06

NLP | Faster Transformer

57:04

3D | Deep Learning for 3D Vision

25:20

Data Visualization | High-Performance, Remote Scientific Visualization in Jupyter Notebooks

21:01

Tabular Data | Google TabNet: Interpretable Tabular Data Learning | AAAI

03:24:11

Meta-Learning | AAAI Tutorial

02:43:11

Deep Learning | Learning with Small Data

03:10:32

Applied AI | Drug Discovery

01:35:16

Deep Learning | Deep Randomized Neural Network

18:19

Time Series | Informer - Beyond Efficient Transformer for Long Sequence Time-Series Forecasting

20:47

Self-Supervised Learning | Curiosity Driven Exploration by Self-Supervised Prediction

01:04:13

Self-Supervised Learning | Self-supervision for Learning from the Bottom Up by Alexei A. Efros

05:14

Representation Learning | Compression with Implicit Neural Representations

13:54

General AI | Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator

01:19:21

Time Series | TS Classification at Scale Geoff Webb | UoA Machine Learning Seminar

19:30

Diabetic Retinopathy Classification using Deep Learning by Mohammad T. Al-Antary

01:36:14

Self-supervised learning in Computer Vision with Yann LeCun, Alfredo Canziani, Ishan Misra

01:12:40

Geometry | Geometric Deep Learning by Michael Bronstein

02:56:56

Interpretability | Interpretability and Analysis in Neural NLP