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Brenden K Petersen

4 papers · 2021–2022 · 3 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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+1 more ↓ 🌍 Conference Polyglot Β· Bronze πŸŒ‰ Interdisciplinary Bridge Β· Silver πŸ—ΊοΈ Taxonomy Completionist (10) 🐣 Hot Topic Early Bird πŸ‘‘ Triple Crown
πŸ“ˆ Trend Setter

Venues

NeurIPS (2) ICLR (1) ICML (1)

Top co-authors

Claudio P Santiago (3) Ruben Glatt (3) Mikel Landajuela (3) Daniel faissol (2) Terrell Mundhenk (2) Joanne Taery Kim (1) Mikel Landajuela Larma (1) Sookyung Kim (1) Jiachen Yang (1) Jacob F Pettit (1)

Research topics

Machine Learning (4) Learning Types Β· Machine Learning (3) Optimization & Theory (3) Deep Learning (2) Mathematics & Optimization (2) Reinforcement Learning (2) Core Methods (2) Methods (2) Models (2) Optimization (2) Artificial Intelligence (1) Core AI (1) Learning Types Β· Deep Learning (1)

Keywords

symbolic regression (3) neural-guided search (2) genetic programming (2) neural network (2) combinatorial optimization (2) hybrid algorithm (1) semantic parsing (1) deep learning (1) autoregressive model (1) recurrent neural network (1) evolutionary algorithm (1) mathematical expression (1) symbolic policy (1) large-scale pretraining (1) program seeding (1) expression discovery (1) risk-seeking policy gradient (1) deep reinforcement learning (1) reinforcement learning (1) black-box optimization (1)

Papers

A Unified Framework for Deep Symbolic Regression NeurIPS 2022 Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients ICLR 2021 Discovering symbolic policies with deep reinforcement learning ICML 2021 Symbolic Regression via Deep Reinforcement Learning Enhanced Genetic Programming Seeding NeurIPS 2021