Daniel D. Johnson

30 papers A* 9C 2Journal 17Unranked 2
YearRankTypeTitle / Venue / Authors
2025 A* conf
Eliciting Language Model Behaviors with Investigator Agents.
ICML
Xiang Lisa Li, Neil Chowdhury, Daniel D. Johnson, Tatsunori Hashimoto, Percy Liang, Sarah Schwettmann, Jacob Steinhardt
2025 J jnl
Eliciting Language Model Behaviors with Investigator Agents.
CoRR
Xiang Lisa Li, Neil Chowdhury, Daniel D. Johnson, Tatsunori Hashimoto, Percy Liang, Sarah Schwettmann, Jacob Steinhardt
2025 J jnl
Predictive Concept Decoders: Training Scalable End-to-End Interpretability Assistants.
CoRR
Vincent Huang, Dami Choi, Daniel D. Johnson, Sarah Schwettmann, Jacob Steinhardt
2024 J jnl
A density estimation perspective on learning from pairwise human preferences.
Trans. Mach. Learn. Res.
Vincent Dumoulin, Daniel D. Johnson, Pablo Samuel Castro, Hugo Larochelle, Yann N. Dauphin
2024 A* conf
Experts Don't Cheat: Learning What You Don't Know By Predicting Pairs.
ICML
Daniel D. Johnson, Daniel Tarlow, David Duvenaud, Chris J. Maddison
2024 J jnl
Experts Don't Cheat: Learning What You Don't Know By Predicting Pairs.
CoRR
Daniel D. Johnson, Daniel Tarlow, David Duvenaud, Chris J. Maddison
2024 J jnl
Parallel Algebraic Effect Handlers.
Proc. ACM Program. Lang.
Ningning Xie, Daniel D. Johnson, Dougal Maclaurin, Adam Paszke
2024 J jnl
Penzai + Treescope: A Toolkit for Interpreting, Visualizing, and Editing Models As Data.
CoRR
Daniel D. Johnson
2023 J jnl
A density estimation perspective on learning from pairwise human preferences.
CoRR
Vincent Dumoulin, Daniel D. Johnson, Pablo Samuel Castro, Hugo Larochelle, Yann N. Dauphin
2023 A* conf
Contrastive Learning Can Find An Optimal Basis For Approximately View-Invariant Functions.
ICLR
Daniel D. Johnson, Ayoub El Hanchi, Chris J. Maddison
2023 A* conf
R-U-SURE? Uncertainty-Aware Code Suggestions By Maximizing Utility Across Random User Intents.
ICML
Daniel D. Johnson, Daniel Tarlow, Christian Walder
2023 J jnl
R-U-SURE? Uncertainty-Aware Code Suggestions By Maximizing Utility Across Random User Intents.
CoRR
Daniel D. Johnson, Daniel Tarlow, Christian Walder
2022 J jnl
A Library for Representing Python Programs as Graphs for Machine Learning.
CoRR
David Bieber, Kensen Shi, Petros Maniatis, Charles Sutton, Vincent J. Hellendoorn, Daniel D. Johnson, Daniel Tarlow
2022 J jnl
Contrastive Learning Can Find An Optimal Basis For Approximately View-Invariant Functions.
CoRR
Daniel D. Johnson, Ayoub El Hanchi, Chris J. Maddison
2021 J jnl
Beyond In-Place Corruption: Insertion and Deletion In Denoising Probabilistic Models.
CoRR
Daniel D. Johnson, Jacob Austin, Rianne van den Berg, Daniel Tarlow
2021 J jnl
Getting to the Point. Index Sets and Parallelism-Preserving Autodiff for Pointful Array Programming.
CoRR
Adam Paszke, Daniel D. Johnson, David Duvenaud, Dimitrios Vytiniotis, Alexey Radul, Matthew J. Johnson, Jonathan Ragan-Kelley, Dougal Maclaurin
2021 J jnl
Getting to the point: index sets and parallelism-preserving autodiff for pointful array programming.
Proc. ACM Program. Lang.
Adam Paszke, Daniel D. Johnson, David Duvenaud, Dimitrios Vytiniotis, Alexey Radul, Matthew J. Johnson, Jonathan Ragan-Kelley, Dougal Maclaurin
2021 A* conf
Learning Generalized Gumbel-max Causal Mechanisms.
NeurIPS
Guy Lorberbom, Daniel D. Johnson, Chris J. Maddison, Daniel Tarlow, Tamir Hazan
2021 J jnl
Learning Generalized Gumbel-max Causal Mechanisms.
CoRR
Guy Lorberbom, Daniel D. Johnson, Chris J. Maddison, Daniel Tarlow, Tamir Hazan
2021 J jnl
Parallel Algebraic Effect Handlers.
CoRR
Ningning Xie, Daniel D. Johnson, Dougal Maclaurin, Adam Paszke
2021 A* conf
Structured Denoising Diffusion Models in Discrete State-Spaces.
NeurIPS
Jacob Austin, Daniel D. Johnson, Jonathan Ho, Daniel Tarlow, Rianne van den Berg
2021 J jnl
Structured Denoising Diffusion Models in Discrete State-Spaces.
CoRR
Jacob Austin, Daniel D. Johnson, Jonathan Ho, Daniel Tarlow, Rianne van den Berg
2020 A* conf
Learning Graph Structure With A Finite-State Automaton Layer.
NeurIPS
Daniel D. Johnson, Hugo Larochelle, Daniel Tarlow
2020 J jnl
Learning Graph Structure With A Finite-State Automaton Layer.
CoRR
Daniel D. Johnson, Hugo Larochelle, Daniel Tarlow
2018 A* conf
Geometric Realizations of the 3D Associahedron (Multimedia Exposition).
SoCG
Satyan L. Devadoss, Daniel D. Johnson, Justin Lee, Jackson Warley
2018 A* conf
Latent Gaussian Activity Propagation: Using Smoothness and Structure to Separate and Localize Sounds in Large Noisy Environments.
NeurIPS
Daniel D. Johnson, Daniel Gorelik, Ross Mawhorter, Kyle Suver, Weiqing Gu, Steven Xing, Cody Gabriel, Peter Sankhagowit
2017 C conf
Generating Polyphonic Music Using Tied Parallel Networks.
EvoMUSART
Daniel D. Johnson
2017 — conf
Learning Graphical State Transitions.
ICLR
Daniel D. Johnson
2017 C conf
Learning to Create Jazz Melodies Using a Product of Experts.
ICCC
Daniel D. Johnson, Robert M. Keller, Nicholas Weintraut
2016 — conf
LEG processor for education.
EWME
Maxwell Waugaman, Zakkai Davidson, Samuel Dietrich, Daniel D. Johnson, Cassandra Meyer, Eric Storm, Avi Thaker, Ivan Wong