David M. Chan

According to our database, David M. Chan authored at least 25 papers between 2004 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

ANIM-400K: A Large-Scale Dataset for Automated End-To-End Dubbing of Video.

Kevin Cai, Chonghua Liu, David M. Chan

CoRR, 2024

Task Oriented Dialogue as a Catalyst for Self-Supervised Automatic Speech Recognition.

David M. Chan, Shalini Ghosh, Hitesh Tulsiani, Ariya Rastrow, Björn Hoffmeister

CoRR, 2024

2023

Multimodal Attention Merging for Improved Speech Recognition and Audio Event Classification.

Anirudh S. Sundar, Chao-Han Huck Yang, David M. Chan, Shalini Ghosh, Venkatesh Ravichandran, Phani Sankar Nidadavolu

CoRR, 2023

IC³: Image Captioning by Committee Consensus.

David M. Chan, Austin Myers, Sudheendra Vijayanarasimhan, David A. Ross, John F. Canny

CoRR, 2023

Using External Off-Policy Speech-To-Text Mappings in Contextual End-To-End Automated Speech Recognition.

David M. Chan, Shalini Ghosh, Ariya Rastrow, Björn Hoffmeister

CoRR, 2023

Domain Adaptation with External Off-Policy Acoustic Catalogs for Scalable Contextual End-to-End Automated Speech Recognition.

David M. Chan, Shalini Ghosh, Ariya Rastrow, Björn Hoffmeister

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Distribution Aware Metrics for Conditional Natural Language Generation.

David M. Chan, Yiming Ni, David A. Ross, Sudheendra Vijayanarasimhan, Austin Myers, John F. Canny

CoRR, 2022

Towards Understanding How Machines Can Learn Causal Overhypotheses.

Eliza Kosoy, David M. Chan, Adrian Liu, Jasmine Collins, Bryanna Kaufmann, Sandy Han Huang, Jessica B. Hamrick, John F. Canny, Nan Rosemary Ke, Alison Gopnik

CoRR, 2022

Content-Context Factorized Representations for Automated Speech Recognition.

David M. Chan, Shalini Ghosh

Proceedings of the Interspeech 2022, 2022

Multi-Modal Pre-Training for Automated Speech Recognition.

David M. Chan, Shalini Ghosh, Debmalya Chakrabarty, Björn Hoffmeister

Proceedings of the IEEE International Conference on Acoustics, 2022

What's in a Caption? Dataset-Specific Linguistic Diversity and Its Effect on Visual Description Models and Metrics.

David M. Chan, Austin Myers, Sudheendra Vijayanarasimhan, David A. Ross, Bryan Seybold, John F. Canny

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Learning Causal Overhypotheses through Exploration in Children and Computational Models.

Eliza Kosoy, Adrian Liu, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Nan Rosemary Ke, Sandy H. Huang, Bryanna Kaufmann, John F. Canny, Alison Gopnik

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

2021

A Semantic Segmentation Network for Urban-Scale Building Footprint Extraction Using RGB Satellite Imagery.

Aatif Jiwani, Shubhrakanti Ganguly, Chao Ding, Nan Zhou, David M. Chan

CoRR, 2021

2020

A Dataset and Benchmarks for Multimedia Social Analysis.

Bofan Xue, David M. Chan, John F. Canny

CoRR, 2020

Exploring Exploration: Comparing Children with RL Agents in Unified Environments.

Eliza Kosoy, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Sandy H. Huang, Alison Gopnik, John F. Canny

CoRR, 2020

Exploring Exploration: Comparing Children with Agents in Unified Exploration Environments.

Eliza Kosoy, Jasmine Collins, David M. Chan, Deepak Pathak, Pulkit Agrawal, Alison Gopnik

Proceedings of the 42th Annual Meeting of the Cognitive Science Society, 2020

Active Learning for Video Description with Cluster-Regularized Ensemble Ranking.

David M. Chan, Sudheendra Vijayanarasimhan, David A. Ross, John F. Canny

Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020

2019

GPU accelerated t-distributed stochastic neighbor embedding.

David M. Chan, Roshan Rao, Forrest Huang, John F. Canny

J. Parallel Distributed Comput., 2019

ZPD Teaching Strategies for Deep Reinforcement Learning from Demonstrations.

Daniel Seita, David M. Chan, Roshan Rao, Chen Tang, Mandi Zhao, John F. Canny

CoRR, 2019

2018

Diagnostic Visualization for Deep Neural Networks Using Stochastic Gradient Langevin Dynamics.

Biye Jiang, David M. Chan, Tianhao Zhang, John F. Canny

CoRR, 2018

Rapid Randomized Restarts for Multi-Agent Path Finding Solvers.

Liron Cohen, Glenn Wagner, David M. Chan, Howie Choset, Nathan R. Sturtevant, Sven Koenig, T. K. Satish Kumar

Proceedings of the Eleventh International Symposium on Combinatorial Search, 2018

T-SNE-CUDA: GPU-Accelerated T-SNE and its Applications to Modern Data.

David M. Chan, Roshan Rao, Forrest Huang, John F. Canny

Proceedings of the 30th International Symposium on Computer Architecture and High Performance Computing, 2018

Rapid Randomized Restarts for Multi-Agent Path Finding: Preliminary Results.

Liron Cohen, Sven Koenig, T. K. Satish Kumar, Glenn Wagner, Howie Choset, David M. Chan, Nathan R. Sturtevant

Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

2017

Using Hierarchical Constraints to Avoid Conflicts in Multi-Agent Pathfinding.

Thayne T. Walker, David M. Chan, Nathan R. Sturtevant

Proceedings of the Twenty-Seventh International Conference on Automated Planning and Scheduling, 2017

2004

Probabilities of extinction, weak extinction, permanence, and mutual exclusion in discrete, competitive, Lotka-Volterra systems that involve invading species.

David M. Chan, J. E. Franke

Math. Comput. Model., 2004