Daniel D. Johnson

30 papers A* 9C 2Journal 17Unranked 2

Year	Rank	Type	Title / 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