David M. Chan

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 39

Top Topics

Speech Recognition

Gpu Accelerated

Stochastic Gradient

Top Venues

Publications

Suzanne Petryk, David M. Chan, Anish Kachinthaya, Haodi Zou, John F. Canny, Joseph E. Gonzalez, Trevor Darrell
ALOHa: A New Measure for Hallucination in Captioning Models. CoRR (2024)
David M. Chan, Shalini Ghosh, Hitesh Tulsiani, Ariya Rastrow, Björn Hoffmeister
Task Oriented Dialogue as a Catalyst for Self-Supervised Automatic Speech Recognition. ICASSP (2024)
David M. Chan, Shalini Ghosh, Hitesh Tulsiani, Ariya Rastrow, Björn Hoffmeister
Task Oriented Dialogue as a Catalyst for Self-Supervised Automatic Speech Recognition. CoRR (2024)
David M. Chan, Yiming Ni, David A. Ross, Sudheendra Vijayanarasimhan, Austin Myers, John F. Canny
Distribution Aware Metrics for Conditional Natural Language Generation. LREC/COLING (2024)
Suhong Moon, Marwa Abdulhai, Minwoo Kang, Joseph Suh, Widyadewi Soedarmadji, Eran Kohen Behar, David M. Chan
Virtual Personas for Language Models via an Anthology of Backstories. CoRR (2024)
Kevin Cai, Chonghua Liu, David M. Chan
Anim-400K: A Large-Scale Dataset for Automated End to End Dubbing of Video. ICASSP (2024)
Yash Jain, David M. Chan, Pranav Dheram, Aparna Khare, Olabanji Shonibare, Venkatesh Ravichandran, Shalini Ghosh
Multi-Stage Multi-Modal Pre-Training for Automatic Speech Recognition. LREC/COLING (2024)
Tsung-Han Wu, Giscard Biamby, Jerome Quenum, Ritwik Gupta, Joseph E. Gonzalez, Trevor Darrell, David M. Chan
Visual Haystacks: Answering Harder Questions About Sets of Images. CoRR (2024)
Kevin Cai, Chonghua Liu, David M. Chan
ANIM-400K: A Large-Scale Dataset for Automated End-To-End Dubbing of Video. CoRR (2024)
Eliza Kosoy, David M. Chan, Adrian Liu, Jasmine Collins, Jessica B. Hamrick, Sandy Han Huang, Nan Rosemary Ke, Emily Rose Reagan, John F. Canny, Alison Gopnik
Towards Understanding How Machines Can Learn Causal Overhypotheses. CogSci (2023)
Anirudh S. Sundar, Chao-Han Huck Yang, David M. Chan, Shalini Ghosh, Venkatesh Ravichandran, Phani Sankar Nidadavolu
Multimodal Attention Merging for Improved Speech Recognition and Audio Event Classification. CoRR (2023)
David M. Chan, Shalini Ghosh, Ariya Rastrow, Björn Hoffmeister
Domain Adaptation with External Off-Policy Acoustic Catalogs for Scalable Contextual End-to-End Automated Speech Recognition. ICASSP (2023)
David M. Chan, Shalini Ghosh, Ariya Rastrow, Björn Hoffmeister
Using External Off-Policy Speech-To-Text Mappings in Contextual End-To-End Automated Speech Recognition. CoRR (2023)
David M. Chan, Austin Myers, Sudheendra Vijayanarasimhan, David A. Ross, John F. Canny
: Image Captioning by Committee Consensus. CoRR (2023)
David M. Chan, Shalini Ghosh, Debmalya Chakrabarty, Björn Hoffmeister
Multi-Modal Pre-Training for Automated Speech Recognition. ICASSP (2022)
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
Towards Understanding How Machines Can Learn Causal Overhypotheses. CoRR (2022)
David M. Chan, Shalini Ghosh
Content-Context Factorized Representations for Automated Speech Recognition. INTERSPEECH (2022)
David M. Chan, Austin Myers, Sudheendra Vijayanarasimhan, David A. Ross, Bryan Seybold, John F. Canny
What's in a Caption? Dataset-Specific Linguistic Diversity and Its Effect on Visual Description Models and Metrics. CVPR Workshops (2022)
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
Learning Causal Overhypotheses through Exploration in Children and Computational Models. CoRR (2022)
David M. Chan, Austin Myers, Sudheendra Vijayanarasimhan, David A. Ross, Bryan Seybold, John F. Canny
What's in a Caption? Dataset-Specific Linguistic Diversity and Its Effect on Visual Description Models and Metrics. CoRR (2022)
Eliza Kosoy, Adrian Liu, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Sandy Han Huang, Nan Rosemary Ke, Bryanna Kaufmann, Alison Gopnik
Learning Causal Overhypotheses through Exploration in Children and Computational Models. CogSci (2022)
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
Learning Causal Overhypotheses through Exploration in Children and Computational Models. CLeaR (2022)
David M. Chan, Yiming Ni, David A. Ross, Sudheendra Vijayanarasimhan, Austin Myers, John F. Canny
Distribution Aware Metrics for Conditional Natural Language Generation. CoRR (2022)
David M. Chan, Shalini Ghosh
Content-Context Factorized Representations for Automated Speech Recognition. CoRR (2022)
David M. Chan, Shalini Ghosh, Debmalya Chakrabarty, Björn Hoffmeister
Multi-Modal Pre-Training for Automated Speech Recognition. CoRR (2021)
Aatif Jiwani, Shubhrakanti Ganguly, Chao Ding, Nan Zhou, David M. Chan
A Semantic Segmentation Network for Urban-Scale Building Footprint Extraction Using RGB Satellite Imagery. CoRR (2021)
David M. Chan, Sudheendra Vijayanarasimhan, David A. Ross, John F. Canny
Active Learning for Video Description with Cluster-Regularized Ensemble Ranking. ACCV (5) (2020)
Eliza Kosoy, Jasmine Collins, David M. Chan, Deepak Pathak, Pulkit Agrawal, Alison Gopnik
Exploring Exploration: Comparing Children with Agents in Unified Exploration Environments. CogSci (2020)
Bofan Xue, David M. Chan, John F. Canny
A Dataset and Benchmarks for Multimedia Social Analysis. CoRR (2020)
David M. Chan, Sudheendra Vijayanarasimhan, David A. Ross, John F. Canny
Active Learning for Video Description With Cluster-Regularized Ensemble Ranking. CoRR (2020)
Eliza Kosoy, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Sandy H. Huang, Alison Gopnik, John F. Canny
Exploring Exploration: Comparing Children with RL Agents in Unified Environments. CoRR (2020)
David M. Chan, Roshan Rao, Forrest Huang, John F. Canny
GPU accelerated t-distributed stochastic neighbor embedding. J. Parallel Distributed Comput. 131 (2019)
Daniel Seita, David M. Chan, Roshan Rao, Chen Tang, Mandi Zhao, John F. Canny
ZPD Teaching Strategies for Deep Reinforcement Learning from Demonstrations. CoRR (2019)
Liron Cohen, Glenn Wagner, David M. Chan, Howie Choset, Nathan R. Sturtevant, Sven Koenig, T. K. Satish Kumar
Rapid Randomized Restarts for Multi-Agent Path Finding Solvers. SOCS (2018)
David M. Chan, Roshan Rao, Forrest Huang, John F. Canny
t-SNE-CUDA: GPU-Accelerated t-SNE and its Applications to Modern Data. CoRR (2018)
David M. Chan, Roshan Rao, Forrest Huang, John F. Canny
T-SNE-CUDA: GPU-Accelerated T-SNE and its Applications to Modern Data. SBAC-PAD (2018)
Liron Cohen, Sven Koenig, T. K. Satish Kumar, Glenn Wagner, Howie Choset, David M. Chan, Nathan R. Sturtevant
Rapid Randomized Restarts for Multi-Agent Path Finding: Preliminary Results. AAMAS (2018)
Biye Jiang, David M. Chan, Tianhao Zhang, John F. Canny
Diagnostic Visualization for Deep Neural Networks Using Stochastic Gradient Langevin Dynamics. CoRR (2018)
Thayne T. Walker, David M. Chan, Nathan R. Sturtevant
Using Hierarchical Constraints to Avoid Conflicts in Multi-Agent Pathfinding. ICAPS (2017)
David M. Chan, J. E. Franke
Probabilities of extinction, weak extinction, permanence, and mutual exclusion in discrete, competitive, Lotka-Volterra systems that involve invading species. Math. Comput. Model. 40 (7-8) (2004)