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Publication search results
found 23 matches
- 2024
- Forest Agostinelli, Rojina Panta, Vedant Khandelwal:
Specifying Goals to Deep Neural Networks with Answer Set Programming. ICAPS 2024: 2-10 - Kausik Lakkaraju, Vedant Khandelwal, Biplav Srivastava, Forest Agostinelli, Hengtao Tang, Prathamjeet Singh, Dezhi Wu, Matthew Irvin, Ashish Kundu:
Trust and ethical considerations in a multi-modal, explainable AI-driven chatbot tutoring system: The case of collaboratively solving Rubik's Cube. CoRR abs/2402.01760 (2024) - Vedant Khandelwal, Amit P. Sheth, Forest Agostinelli:
Towards Learning Foundation Models for Heuristic Functions to Solve Pathfinding Problems. CoRR abs/2406.02598 (2024) - 2023
- Hamed Damirchi, Forest Agostinelli, Pooyan Jamshidi:
Independent Modular Networks. CoRR abs/2306.01316 (2023) - Bharath Muppasani, Vishal Pallagani, Biplav Srivastava, Forest Agostinelli:
On Solving the Rubik's Cube with Domain-Independent Planners Using Standard Representations. CoRR abs/2307.13552 (2023) - 2022
- Muntaha Samad, Forest Agostinelli, Tomoki Sato, Kohei Shimaji, Pierre Baldi:
CircadiOmics: circadian omic web portal. Nucleic Acids Res. 50(W1): 183-190 (2022) - Kausik Lakkaraju, Thahimum Hassan, Vedant Khandelwal, Prathamjeet Singh, Cassidy Bradley, Ronak Shah, Forest Agostinelli, Biplav Srivastava, Dezhi Wu:
ALLURE: A Multi-Modal Guided Environment for Helping Children Learn to Solve a Rubik's Cube with Automatic Solving and Interactive Explanations. AAAI 2022: 13185-13187 - Cassidy Bradley, Dezhi Wu, Hengtao Tang, Ishu Singh, Katelyn Wydant, Brittany Capps, Karen Wong, Forest Agostinelli, Matthew Irvin, Biplav Srivastava:
Explainable Artificial Intelligence (XAI) User Interface Design for Solving a Rubik's Cube. HCI (49) 2022: 605-612 - Dezhi Wu, Hengtao Tang, Cassidy Bradley, Brittany Capps, Prathamjeet Singh, Katelyn Wyandt, Karen Wong, Matthew Irvin, Forest Agostinelli, Biplav Srivastava:
AI-Driven User Interface Design for Solving a Rubik's Cube: A Scaffolding Design Perspective. HCI (41) 2022: 490-498 - 2021
- Mohammadamin Tavakoli, Forest Agostinelli, Pierre Baldi:
SPLASH: Learnable activation functions for improving accuracy and adversarial robustness. Neural Networks 140: 1-12 (2021) - Forest Agostinelli, Mihir Mavalankar, Vedant Khandelwal, Hengtao Tang, Dezhi Wu, Barnett Berry, Biplav Srivastava, Amit P. Sheth, Matthew Irvin:
Designing Children's New Learning Partner: Collaborative Artificial Intelligence for Learning to Solve the Rubik's Cube. IDC 2021: 610-614 - Forest Agostinelli, Alexander Shmakov, Stephen McAleer, Roy Fox, Pierre Baldi:
A* Search Without Expansions: Learning Heuristic Functions with Deep Q-Networks. CoRR abs/2102.04518 (2021) - 2020
- Mohammadamin Tavakoli, Forest Agostinelli, Pierre Baldi:
SPLASH: Learnable Activation Functions for Improving Accuracy and Adversarial Robustness. CoRR abs/2006.08947 (2020) - 2019
- Forest Agostinelli, Stephen McAleer, Alexander Shmakov, Pierre Baldi:
Solving the Rubik's cube with deep reinforcement learning and search. Nat. Mach. Intell. 1(8): 356-363 (2019) - Stephen McAleer, Forest Agostinelli, Alexander Shmakov, Pierre Baldi:
Solving the Rubik's Cube with Approximate Policy Iteration. ICLR (Poster) 2019 - 2018
- Nicholas Ceglia, Yu Liu, Siwei Chen, Forest Agostinelli, Kristin Eckel-Mahan, Paolo Sassone-Corsi, Pierre Baldi:
CircadiOmics: circadian omic web portal. Nucleic Acids Res. 46(Webserver-Issue): W157-W162 (2018) - Stephen McAleer, Forest Agostinelli, Alexander Shmakov, Pierre Baldi:
Solving the Rubik's Cube Without Human Knowledge. CoRR abs/1805.07470 (2018) - 2017
- Forest Agostinelli, Guillaume Hocquet, Sameer Singh, Pierre Baldi:
From Reinforcement Learning to Deep Reinforcement Learning: An Overview. Braverman Readings in Machine Learning 2017: 298-328 - 2016
- Forest Agostinelli, Nicholas Ceglia, Babak Shahbaba, Paolo Sassone-Corsi, Pierre Baldi:
What time is it? Deep learning approaches for circadian rhythms. Bioinform. 32(12): 8-17 (2016) - Forest Agostinelli, Nicholas Ceglia, Babak Shahbaba, Paolo Sassone-Corsi, Pierre Baldi:
What time is it? Deep learning approaches for circadian rhythms. Bioinform. 32(19): 3051 (2016) - Tianlin Shi, Forest Agostinelli, Matthew Staib, David P. Wipf, Thomas Moscibroda:
Improving Survey Aggregation with Sparsely Represented Signals. KDD 2016: 1845-1854 - 2015
- Forest Agostinelli, Matthew D. Hoffman, Peter J. Sadowski, Pierre Baldi:
Learning Activation Functions to Improve Deep Neural Networks. ICLR (Workshop) 2015 - 2013
- Forest Agostinelli, Michael R. Anderson, Honglak Lee:
Adaptive Multi-Column Deep Neural Networks with Application to Robust Image Denoising. NIPS 2013: 1493-1501
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