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Tue Dec 14 03:45 AM -- 03:00 PM (PST)
Advances in Programming Languages and Neurosymbolic Systems (AIPLANS)
Breandan Considine · Disha Shrivastava · David Yu-Tung Hui · Chin-Wei Huang · Shawn Tan · Xujie Si · Prakash Panangaden · Guy Van den Broeck · Daniel Tarlow

Workshop Home Page

Neural information processing systems have benefited tremendously from the availability of programming languages and frameworks for automatic differentiation (AD). Not only do NeurIPS benefit from programming languages for automatic inference but can also be considered as a language in their own right, consisting of differentiable and stochastic primitives. Combined with neural language models, these systems are increasingly capable of generating symbolic programs a human programmer might write in a high-level language. Developing neurosymbolic systems for automatic program synthesis requires insights from both statistical learning and programming languages.

AIPLANS invites all researchers working towards the same purpose in these two communities to build on common ground. Our workshop is designed to be as inclusive as possible towards researchers engaged in building programming languages and neurosymbolic systems.

Introductory remarks (Introductory Remarks)
Thinking like Transformers - Gail Weiss - Technion - Israel Institute of Technology (Invited Talk)
When Gödel discovered Automatic Differentiation - Marie Kerjean - Laboratoire d'Informatique de Paris Nord (Invited Talk)
Joshua Tenenbaum Massachusetts Institute of Technology (Invited Talk)
Panel Discussion
Daniel Selsam Microsoft Research (Tutorial)
Lunch / Poster Session (Poster Session)
Randomized Automatic Differentiation - Ryan Adams - Princeton University (Invited Talk)
David Duvenaud University of Toronto (Invited Talk)
Differential Inference: A Criminally Underused Tool. - Alexander Rush - Cornell University (Invited Talk)
Spotlight Talks from Authors 1 (Spotlight Talks)
Spotlight Talks from Authors 2 (Spotlight Talk)
Spotlight Talks from Authors 3 (Spotlight Talks)
Spotlight Talks from Authors 4 (Spotlight Talk)
Spotlight Talks from Authors 5 (Spotlight Talk)
Poster Session
Proof Extraction for Logical Neural Networks (Poster)
Synthesizing Video Trajectory Queries (Poster)
A Genetic Programming Approach To Zero-Shot Neural Architecture Ranking (Poster)
Safe Neurosymbolic Learning with Differentiable Symbolic Execution (Poster)
Are Transformers All That Karel Needs? (Poster)
AutumnSynth: Synthesis of Reactive Programs with Structured Latent State (Poster)
Learning C to x86 Translation: An Experiment in Neural Compilation (Poster)
AutoCoder: Leveraging Transformers for Automatic Code Synthesis (Poster)
Adversarial Robustness of Program Synthesis Models (Poster)
Learning Adaptive Control Flow in Transformers for Improved Systematic Generalization (Poster)
Meta-Learning an Inference Algorithm for Probabilistic Programs (Poster)
Towards Neural Functional Program Evaluation (Poster)
PAC Synthesis of Machine Learning Programs (Poster)
Scallop: From Probabilistic Deductive Databases to Scalable Differentiable Reasoning (Poster)
Type Inference as Optimization (Poster)
Augmenting Classic Algorithms with Neural Components for Strong Generalisation on Ambiguous and High-Dimensional Data (Poster)
Staged compilation of tensor expressions (Poster)
LazyPPL: laziness and types in non-parametric probabilistic programs (Poster)
Learning compositional programs with arguments and sampling (Poster)
Learning Rules with Stratified Negation in Differentiable ILP. (Poster)