T. Nathan Mundhenk

Publication Activity (10 Years)

Years Active: 2002-2023
Publications (10 Years): 17

Top Topics

Policy Gradient

Symbolic Regression

Top Venues

Intelligent Robots and Computer Vision: Algorithms and Techniques

Publications

Fabrício Olivetti de França, Marco Virgolin, Michael Kommenda, M. S. Majumder, Miles D. Cranmer, Guilherme Espada, Leon Ingelse, Alcides Fonseca, Mikel Landajuela, B. Petersen, Ruben Glatt, T. Nathan Mundhenk, C. S. Lee, Jacob D. Hochhalter, David L. Randall, P. Kamienny, H. Zhang, G. Dick, A. Simon, Bogdan Burlacu, Jaan Kasak, Meera Vieira Machado, Casper Wilstrup, William G. La Cava
Interpretable Symbolic Regression for Data Science: Analysis of the 2022 Competition. CoRR (2023)
T. Nathan Mundhenk, Mikel Landajuela, Ruben Glatt, Cláudio P. Santiago, Daniel M. Faissol, Brenden K. Petersen
Symbolic Regression via Neural-Guided Genetic Programming Population Seeding. CoRR (2021)
Mikel Landajuela Larma, Brenden K. Petersen, Sookyung Kim, Cláudio P. Santiago, Ruben Glatt, T. Nathan Mundhenk, Jacob F. Pettit, Daniel Faissol
Discovering symbolic policies with deep reinforcement learning. ICML (2021)
T. Nathan Mundhenk, Mikel Landajuela, Ruben Glatt, Cláudio P. Santiago, Daniel M. Faissol, Brenden K. Petersen
Symbolic Regression via Deep Reinforcement Learning Enhanced Genetic Programming Seeding. NeurIPS (2021)
Brenden K. Petersen, Mikel Landajuela Larma, T. Nathan Mundhenk, Cláudio Prata Santiago, Sookyung Kim, Joanne Taery Kim
Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients. ICLR (2021)
Ian A. Palmer, T. Nathan Mundhenk, Brian Gallagher, Yong Han
Explaining neural network predictions of material strength. CoRR (2021)
Mikel Landajuela Larma, Brenden K. Petersen, Soo K. Kim, Cláudio P. Santiago, Ruben Glatt, T. Nathan Mundhenk, Jacob F. Pettit, Daniel M. Faissol
Improving exploration in policy gradient search: Application to symbolic optimization. CoRR (2021)
Gerald Friedland, Ruoxi Jia, Jingkang Wang, Bo Li, T. Nathan Mundhenk
On the Impact of Perceptual Compression on Deep Learning. MIPR (2020)
T. Nathan Mundhenk, Barry Y. Chen, Gerald Friedland
Efficient Saliency Maps for Explainable AI. CoRR (2019)
T. Nathan Mundhenk, Daniel Ho, Barry Y. Chen
Improvements to Context Based Self-Supervised Learning. CVPR (2018)
T. Nathan Mundhenk, Laura M. Kegelmeyer, Scott K. Trummer
Deep learning for evaluating difficult-to-detect incomplete repairs of high fluence laser optics at the National Ignition Facility. QCAV (2017)
Wesam A. Sakla, Goran Konjevod, T. Nathan Mundhenk
Deep Multi-modal Vehicle Detection in Aerial ISR Imagery. WACV (2017)
T. Nathan Mundhenk, Daniel Ho, Barry Y. Chen
Improvements to context based self-supervised learning. CoRR (2017)
T. Nathan Mundhenk, Goran Konjevod, Wesam A. Sakla, Kofi Boakye
A Large Contextual Dataset for Classification, Detection and Counting of Cars with Deep Learning. CoRR (2016)
T. Nathan Mundhenk, Goran Konjevod, Wesam A. Sakla, Kofi Boakye
A Large Contextual Dataset for Classification, Detection and Counting of Cars with Deep Learning. ECCV (3) (2016)
Jun Sawada, Filipp Akopyan, Andrew S. Cassidy, Brian Taba, Michael V. DeBole, Pallab Datta, Rodrigo Alvarez-Icaza, Arnon Amir, John V. Arthur, Alexander Andreopoulos, Rathinakumar Appuswamy, Heinz Baier, Davis Barch, David J. Berg, Carmelo di Nolfo, Steven K. Esser, Myron Flickner, Thomas A. Horvath, Bryan L. Jackson, Jeff Kusnitz, Scott Lekuch, Michael Mastro, Timothy Melano, Paul A. Merolla, Steven E. Millman, Tapan K. Nayak, Norm Pass, Hartmut E. Penner, William P. Risk, Kai Schleupen, Benjamin Shaw, Hayley Wu, Brian Giera, Adam T. Moody, T. Nathan Mundhenk, Brian Van Essen, Eric X. Wang, David P. Widemann, Qing Wu, William E. Murphy, Jamie K. Infantolino, James A. Ross, Dale R. Shires, Manuel M. Vindiola, Raju Namburu, Dharmendra S. Modha
Truenorth ecosystem for brain-inspired computing: scalable systems, software, and applications. SC (2016)
T. Nathan Mundhenk, Kyungnam Kim, Yuri Owechko
PanDAR: a wide-area, frame-rate, and full color lidar with foveated region using backfilling interpolation upsampling. Intelligent Robots and Computer Vision: Algorithms and Techniques (2015)
T. Nathan Mundhenk, Kyungnam Kim, Yuri Owechko
Frame Rate Fusion and Upsampling of EO/LIDAR Data for Multiple Platforms. CVPR Workshops (2014)
T. Nathan Mundhenk, Arturo Flores, Heiko Hoffman
Classification and segmentation of orbital space based objects against terrestrial distractors for the purpose of finding holes in shape from motion 3D reconstruction. Intelligent Robots and Computer Vision: Algorithms and Techniques (2014)
Mike Howard, Rashmi Sundareswara, Mike Daily, Rajan Bhattacharyya, Sam Kaplan, T. Nathan Mundhenk, Craig Lee, Howard Neely
Using tactile displays to maintain situational awareness during driving. CogSIMA (2013)
T. Nathan Mundhenk, Kang-Yu Ni, Yang Chen, Kyungnam Kim, Yuri Owechko
Detection of unknown targets from aerial camera and extraction of simple object fingerprints for the purpose of target reacquisition. Intelligent Robots and Computer Vision: Algorithms and Techniques (2012)
T. Nathan Mundhenk, Rashmi Sundareswara, David R. Gerwe, Yang Chen
High precision object segmentation and tracking for use in super resolution video reconstruction. Intelligent Robots and Computer Vision: Algorithms and Techniques (2011)
T. Nathan Mundhenk, Laurent Itti
Computational modeling and exploration of contour integration for visual saliency. Biol. Cybern. 93 (3) (2005)
T. Nathan Mundhenk, Vidhya Navalpakkam, Hendrik Makaliwe, Shrihari Vasudevan, Laurent Itti
Biologically inspired feature-based categorization of objects. Human Vision and Electronic Imaging (2004)
T. Nathan Mundhenk, Laurent Itti
CINNIC, a new computational algorithm for the modeling of early visual contour integration in humans. Neurocomputing (2003)
Daesu Chung, Reid Hirata, T. Nathan Mundhenk, Jen Ng, Robert J. Peters, Eric Pichon, April Tsui, Tong Ventrice, Dirk Walther, Philip Williams, Laurent Itti
A New Robotics Platform for Neuromorphic Vision: Beobots. Biologically Motivated Computer Vision (2002)
T. Nathan Mundhenk, Laurent Itti
A Model of Contour Integration in Early Visual Cortex. Biologically Motivated Computer Vision (2002)