Daniel Huang

22 papers A* 2A 1B 1Journal 15Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
Scaling Gaussian Process Regression with Full Derivative Observations.
Trans. Mach. Learn. Res.
Daniel Huang
2025 J jnl
Circuit Partitioning and Full Circuit Execution: A Comparative Study of GPU-Based Quantum Circuit Simulation.
CoRR
Kartikey Sarode, Daniel Huang, E. Wes Bethel
2025 J jnl
From Bits to Qubits: Challenges in Classical-Quantum Integration.
CoRR
Sudhanshu Pravin Kulkarni, Daniel Huang, E. Wes Bethel
2025 J jnl
High-Dimensional Gaussian Process Regression with Soft Kernel Interpolation.
Trans. Mach. Learn. Res.
Christian Camaño, Daniel Huang
2025 J jnl
Scaling Gaussian Process Regression with Full Derivative Observations.
CoRR
Daniel Huang
2024 J jnl
High-Dimensional Gaussian Process Regression with Soft Kernel Interpolation.
CoRR
Christian Camaño, Daniel Huang
2023 J jnl
On Training Derivative-Constrained Neural Networks.
CoRR
KaiChieh Lo, Daniel Huang
2023 J jnl
PusH: Concurrent Probabilistic Programming with Function Spaces.
CoRR
Daniel Huang, Christian Camaño, Jonathan Tsegaye
2023 J jnl
Quantum Computing and Visualization: A Disruptive Technological Change Ahead.
IEEE Computer Graphics and Applications
E. Wes Bethel, Mercy G. Amankwah, Jan Balewski, Roel Van Beeumen, Daan Camps, Daniel Huang, Talita Perciano
2023 J jnl
Quantum Computing and Visualization: A Disruptive Technological Change Ahead.
CoRR
E. Wes Bethel, Mercy G. Amankwah, Jan Balewski, Roel Van Beeumen, Daan Camps, Daniel Huang, Talita Perciano
2020 — ch.
Application ofComputable Distributions to the Semantics of Probabilistic Programs.
Foundations of Probabilistic Programming
Daniel Huang, Greg Morrisett, Bas Spitters
2020 J jnl
Elementary Logic in Linear Space.
CoRR
Daniel Huang
2019 — conf
GamePad: A Learning Environment for Theorem Proving.
ICLR (Poster)
Daniel Huang, Prafulla Dhariwal, Dawn Song, Ilya Sutskever
2019 J jnl
On Learning to Prove.
CoRR
Daniel Huang
2018 J jnl
An Application of Computable Distributions to the Semantics of Probabilistic Programs.
CoRR
Daniel Huang, Greg Morrisett, Bas Spitters
2018 J jnl
GamePad: A Learning Environment for Theorem Proving.
CoRR
Daniel Huang, Prafulla Dhariwal, Dawn Song, Ilya Sutskever
2017 A* conf
Compiling Markov chain Monte Carlo algorithms for probabilistic modeling.
PLDI
Daniel Huang, Jean-Baptiste Tristan, Greg Morrisett
2016 A conf
An Application of Computable Distributions to the Semantics of Probabilistic Programming Languages.
ESOP
Daniel Huang, Greg Morrisett
2014 — conf
Augur: Data-Parallel Probabilistic Modeling.
NIPS
Jean-Baptiste Tristan, Daniel Huang, Joseph Tassarotti, Adam Craig Pocock, Stephen J. Green, Guy L. Steele Jr.
2013 J jnl
Augur: a Modeling Language for Data-Parallel Probabilistic Inference.
CoRR
Jean-Baptiste Tristan, Daniel Huang, Joseph Tassarotti, Adam Craig Pocock, Stephen J. Green, Guy L. Steele Jr.
2013 B conf
Formalizing the SAFECode Type System.
CPP
Daniel Huang, Greg Morrisett
2011 A* conf
Segmentation fusion for connectomics.
ICCV
Amelio Vázquez Reina, Michael Gelbart, Daniel Huang, Jeff Lichtman, Eric L. Miller, Hanspeter Pfister