Felipe Petroski Such

Publications by Year

Research Areas

Reinforcement Learning in Robotics, Topic Modeling, Advanced Neural Network Applications, Domain Adaptation and Few-Shot Learning, Adversarial Robustness in Machine Learning

Most-Cited Works

• → Evaluating Large Language Models Trained on Code(2021)1,403 cited
• → An Intriguing Failing of Convolutional Neural Networks and the CoordConv\n Solution(2018)645 cited
• → Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning(2017)554 cited
• → Intelligent character recognition using fully convolutional neural networks(2018)166 cited
• → Text and Code Embeddings by Contrastive Pre-Training(2022)148 cited
• Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents(2018)
• → Robust Spatial Filtering With Graph Convolutional Neural Networks(2017)146 cited
• → Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data(2019)48 cited