1:03:41A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks
A 64-minute video from Physics Meets ML: “A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks”.
Physics Meets ML
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1:03:41
1:11:07A self-consistent GP framework far from the GP limit
A 71-minute video from Physics Meets ML: “A self-consistent GP framework far from the GP limit”.
1:06:03Algebraic Neural Networks
A 66-minute video from Physics Meets ML: “Algebraic Neural Networks”.
1:00:54Anomaly detection in the search for new physics
A 61-minute video from Physics Meets ML: “Anomaly detection in the search for new physics”.
1:12:39Are wider nets better given the same number of parameters?
A 73-minute video from Physics Meets ML: “Are wider nets better given the same number of parameters?”.
1:25:00BI for AI: Energy conserving descent for optimization
A 85-minute video from Physics Meets ML: “BI for AI: Energy conserving descent for optimization”.
1:11:50Building symmetries into generative flow models
A 72-minute video from Physics Meets ML: “Building symmetries into generative flow models”.
1:09:14Compositionality of Symmetry in Equivariant Multilayer Perceptrons
A 69-minute video from Physics Meets ML: “Compositionality of Symmetry in Equivariant Multilayer Perceptrons”.
1:25:13Deep Learning and Quantum Gravity
A 85-minute video from Physics Meets ML: “Deep Learning and Quantum Gravity”.
1:10:39Deep Neural Networks for Ab Initio Quantum Chemistry
A 71-minute video from Physics Meets ML: “Deep Neural Networks for Ab Initio Quantum Chemistry”.
1:00:02Differentiable Physics Simulations for Deep Learning
A 60-minute video from Physics Meets ML: “Differentiable Physics Simulations for Deep Learning”.
1:03:47Differentiable Programming in HEP
A 64-minute video from Physics Meets ML: “Differentiable Programming in HEP”.
1:08:27Discovering new phases of matter with unsupervised and interpretable support vector machines
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A 68-minute video from Physics Meets ML: “Discovering new phases of matter with unsupervised and interpretable support vector machines”.
1:19:16Effective Theory of Deep Neural Networks
A 79-minute video from Physics Meets ML: “Effective Theory of Deep Neural Networks”.
1:18:39Equivariant Neural Fields: A Roadmap Towards Generalizable Neural Representation and Inference
A 79-minute video from Physics Meets ML: “Equivariant Neural Fields: A Roadmap Towards Generalizable Neural Representation and Inference”.
1:06:02Euclidean Neural Networks: Adventures in learning with 3D geometry and geometric tensors.
A 66-minute video from Physics Meets ML: “Euclidean Neural Networks: Adventures in learning with 3D geometry and geometric tensors.”.
1:01:56Explainable deep learning models for cosmological structure formation
A 62-minute video from Physics Meets ML: “Explainable deep learning models for cosmological structure formation”.
1:17:52Explaining Neural Scaling Laws
A 78-minute video from Physics Meets ML: “Explaining Neural Scaling Laws”.
1:25:41Explorations at the Physics ∩ ML Interface
A 86-minute video from Physics Meets ML: “Explorations at the Physics ∩ ML Interface”.
1:14:48Fast and Credible Inference with Truncated Marginal Neural Ratio Estimation
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A 75-minute video from Physics Meets ML: “Fast and Credible Inference with Truncated Marginal Neural Ratio Estimation”.
2:09:49Feature Learning in Infinite-Width Neural Networks
A 130-minute video from Physics Meets ML: “Feature Learning in Infinite-Width Neural Networks”.
1:07:17Flow-based likelihoods for non-Gaussian inference
A 67-minute video from Physics Meets ML: “Flow-based likelihoods for non-Gaussian inference”.
1:04:17Formal Mathematics Statement Curriculum Learning
A 64-minute video from Physics Meets ML: “Formal Mathematics Statement Curriculum Learning”.
1:08:16Harnessing Data Revolution in Quantum Matter
A 68-minute video from Physics Meets ML: “Harnessing Data Revolution in Quantum Matter”.
1:06:38Implicit Regularization in Quantum Tensor Networks
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A 67-minute video from Physics Meets ML: “Implicit Regularization in Quantum Tensor Networks”.
1:28:48Insights on gradient-based algorithms in high-dimensional learning
A 89-minute video from Physics Meets ML: “Insights on gradient-based algorithms in high-dimensional learning”.
1:08:36Interpretable Deep Learning for Physics
A 69-minute video from Physics Meets ML: “Interpretable Deep Learning for Physics”.
1:33:38JAX MD: A Framework for Differentiable Atomistic Physics
A 94-minute video from Physics Meets ML: “JAX MD: A Framework for Differentiable Atomistic Physics”.
1:01:23Learning for Safety-Critical Control in Dynamical Systems
A 61-minute video from Physics Meets ML: “Learning for Safety-Critical Control in Dynamical Systems”.
1:00:00Machine Learning Application for the Event Horizon Telescope
A 60-minute video from Physics Meets ML: “Machine Learning Application for the Event Horizon Telescope”.
1:04:47Machine Learning Statistical Gravity from Multi-Region Entanglement Entropy
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A 65-minute video from Physics Meets ML: “Machine Learning Statistical Gravity from Multi-Region Entanglement Entropy”.
1:13:09Machine Learning for Calabi-Yau metrics
A 73-minute video from Physics Meets ML: “Machine Learning for Calabi-Yau metrics”.
1:04:08Machine learning as a discovery tool in hep-th
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A 64-minute video from Physics Meets ML: “Machine learning as a discovery tool in hep-th”.
1:15:35Maths with transformers
A 76-minute video from Physics Meets ML: “Maths with transformers”.
1:22:44Minerva: Solving Quantitative Reasoning Problems with Language Models
A 83-minute video from Physics Meets ML: “Minerva: Solving Quantitative Reasoning Problems with Language Models”.
1:26:55Natural Graph Networks
A 87-minute video from Physics Meets ML: “Natural Graph Networks”.