Daniel Huang

Orcid: 0000-0002-1949-1116

Affiliations:
  • San Francisco State University, Language-Based Artificial Intelligence (LBAI) Lab, CA, USA
  • University of California, Berkeley, Department of Electrical Engineering and Computer Sciences, CA, USA (former)
  • Harvard University, School of Engineering and Applied Sciences, Cambridge, MA, USA (PhD)


According to our database1, Daniel Huang authored at least 13 papers between 2011 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
On Training Derivative-Constrained Neural Networks.
CoRR, 2023

PusH: Concurrent Probabilistic Programming with Function Spaces.
CoRR, 2023

Quantum Computing and Visualization: A Disruptive Technological Change Ahead.
IEEE Computer Graphics and Applications, 2023

2020
Elementary Logic in Linear Space.
CoRR, 2020

2019
On Learning to Prove.
CoRR, 2019

GamePad: A Learning Environment for Theorem Proving.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
An Application of Computable Distributions to the Semantics of Probabilistic Programs.
CoRR, 2018

2017
Compiling Markov chain Monte Carlo algorithms for probabilistic modeling.
Proceedings of the 38th ACM SIGPLAN Conference on Programming Language Design and Implementation, 2017

2016
An Application of Computable Distributions to the Semantics of Probabilistic Programming Languages.
Proceedings of the Programming Languages and Systems, 2016

2014
Augur: Data-Parallel Probabilistic Modeling.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013
Augur: a Modeling Language for Data-Parallel Probabilistic Inference.
CoRR, 2013

Formalizing the SAFECode Type System.
Proceedings of the Certified Programs and Proofs - Third International Conference, 2013

2011
Segmentation fusion for connectomics.
Proceedings of the IEEE International Conference on Computer Vision, 2011


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