Bridging Informal and Formal Mathematical Reasoning with Neural Language Models
Neurosymbolic Programming for Science
Bridging Informal and Formal Mathematical Reasoning with Neural Language Models
1:06:09
AI for Scientists: Accelerating Discovery through Knowledge, Data & Learning
Neurosymbolic Programming for Science
AI for Scientists: Accelerating Discovery through Knowledge, Data & Learning
53:31
Probabilistic Programming Tutorial Part 1
Neurosymbolic Programming for Science
Probabilistic Programming Tutorial Part 1
1:06:51
Model Based Reasoning
Neurosymbolic Programming for Science
Model Based Reasoning
43:11
Probabilistic Programming Tutorial Part 2
Neurosymbolic Programming for Science
Probabilistic Programming Tutorial Part 2
1:10:58
Moving Beyond the First Portrait of Our Milky Way’s Black Hole by Leveraging Underlying Structure
Neurosymbolic Programming for Science
Moving Beyond the First Portrait of Our Milky Way’s Black Hole by Leveraging Underlying Structure
59:04
Neurosymbolic Program Architecture Search (continued)
Neurosymbolic Programming for Science
Neurosymbolic Program Architecture Search (continued)
35:20
Understanding the Visual World Through Naturally Supervised Code
Neurosymbolic Programming for Science
Understanding the Visual World Through Naturally Supervised Code
1:12:35
Tutorial on Deductive Program Synthesis Part 2
Neurosymbolic Programming for Science
Tutorial on Deductive Program Synthesis Part 2
41:57
Better learning through Programming Languages
Neurosymbolic Programming for Science
Better learning through Programming Languages
1:13:21
Neurosymbolic Program Architecture Search
Neurosymbolic Programming for Science
Neurosymbolic Program Architecture Search
43:09
Competitive Programming with AlphaCode
Neurosymbolic Programming for Science
Competitive Programming with AlphaCode
56:46
Programming with Neural Surrogates of Programs
Neurosymbolic Programming for Science
Programming with Neural Surrogates of Programs
1:06:21
Workshop 4: Generating code that activates our brains
Neurosymbolic Programming for Science
Workshop 4: Generating code that activates our brains
2:13:27
Workshop 3 - Learning to automatically fix compiler errors in C
Neurosymbolic Programming for Science
Workshop 3 - Learning to automatically fix compiler errors in C
2:26:21
Workshop 2: An Introduction to Symbolic Regression with PySR and SymbolicRegression.jl
Neurosymbolic Programming for Science
Workshop 2: An Introduction to Symbolic Regression with PySR and SymbolicRegression.jl
2:24:36
Workshop 1: Data-Efficient Graph Grammar Learning for Molecular Generation
Neurosymbolic Programming for Science
Workshop 1: Data-Efficient Graph Grammar Learning for Molecular Generation
1:07:39
Tutorial 1b: SuSLik: deductive synthesisof safe programs with pointers
Neurosymbolic Programming for Science
Tutorial 1b: SuSLik: deductive synthesisof safe programs with pointers
40:49
Tutorial 1a: Basics of Neurosymbolic Architectures
Neurosymbolic Programming for Science
Tutorial 1a: Basics of Neurosymbolic Architectures
34:14
AI for code and science - Omar Costilla-Reyes, PhD
Neurosymbolic Programming for Science
AI for code and science - Omar Costilla-Reyes, PhD
43:10
Jacob Andreas: Toward Natural Language Supervision
Neurosymbolic Programming for Science
Jacob Andreas: Toward Natural Language Supervision
1:05:58
Introductory remarks - Armando Solar-Lezama
Neurosymbolic Programming for Science
Introductory remarks - Armando Solar-Lezama
4:15
Competition-Level Code Generation with AlphaCode
Neurosymbolic Programming for Science
Competition-Level Code Generation with AlphaCode
1:06:55
Outracing champion Gran Turismo drivers with deep reinforcement learning
Neurosymbolic Programming for Science
Outracing champion Gran Turismo drivers with deep reinforcement learning
1:02:50
Construction of mental representations in human planning
Neurosymbolic Programming for Science
Construction of mental representations in human planning
58:06
Differentiable Programming via Differentiable Search of Program Structures
Neurosymbolic Programming for Science
Differentiable Programming via Differentiable Search of Program Structures
58:16
Bayesian symbolic regression and the learnability of closed-form mathematical models
Neurosymbolic Programming for Science
Bayesian symbolic regression and the learnability of closed-form mathematical models
48:46
Analysis of 6.4 million SARS-CoV-2 genomes identifies mutations associated with fitness
Neurosymbolic Programming for Science
Analysis of 6.4 million SARS-CoV-2 genomes identifies mutations associated with fitness
59:15