David Duvenaud
- Neural Ordinary Differential Equations
2018/06/19 by Ricky T. Q. Chen, Chen, Ricky T. Q., Yulia Rubanova +5 · 5 voices · 553 citations
Physics and Astronomy · Computer Science · #Model Reduction and Neural Networks #Generative Adversarial Networks and Image Synthesis #Computational Physics and Python Applications
- AI Supported Degradation of the Self Concept: A Theoretical Framework Grounded in Established Cognitive and Computational Mechanisms
2023/10/20 by Mrinank Sharma, Sharma, Mrinank, Meg Tong +36 · 10 voices · 226 citations
Computer Science · #Explainable Artificial Intelligence (XAI) #Reinforcement Learning in Robotics #Topic Modeling #cs.AI #cs.CL #cs.LG #stat.ML
- Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training
2024/01/10 by Evan Hubinger, Carson Denison, Hubinger, Evan +77 · 18 voices · 98 citations
Computer Science · Social Sciences · #Adversarial Robustness in Machine Learning #Ethics and Social Impacts of AI #Topic Modeling #cs.AI #cs.CL #cs.CR #cs.LG #cs.SE
- Gradual Disempowerment: Systemic Existential Risks from Incremental AI Development
2025/01/28 by Jan Kulveit, Raymond Douglas, Kulveit, Jan +10 · 21 voices · 20 citations
Social Sciences · #Ethics and Social Impacts of AI
- A Definition of AGI
2025/10/21 by Dan Hendrycks, Hendrycks, Dan, Dawn Song +65 · 28 voices · 10 citations
Psychology · Computer Science · #Cognitive Abilities and Testing #Computability, Logic, AI Algorithms #Cognitive Computing and Networks
- Los carnavales de La Bañeza: Aspectos antropológicos
1976/01/01 by Rafael Gómez-Bombarelli, Jennifer N. Wei, David Duvenaud +8 · 2 voices · 70 citations
Arts and Humanities · Computer Science · Environmental Science · Materials Science · #Chemistry and Chemical Engineering #Computational Drug Discovery Methods #Cultural and Mythological Studies #Historical and Literary Analyses #Machine Learning in Materials Science #Spanish Literature and Culture Studies #cs.LG #physics.chem-ph
- Gradient-based Hyperparameter Optimization through Reversible Learning
2015/02/11 by Dougal Maclaurin, David Duvenaud, Maclaurin, Dougal +3 · 1 voice · 41 citations
Computer Science · #Machine Learning and Data Classification #Gaussian Processes and Bayesian Inference #Advanced Neural Network Applications
- Alignment faking in large language models
2024/12/18 by Ryan Greenblatt, Carson Denison, Greenblatt, Ryan +38 · 16 voices · 62 citations
Computer Science · #Natural Language Processing Techniques #Topic Modeling #cs.AI #cs.CL #cs.LG
- Who's in Charge? Disempowerment Patterns in Real-World LLM Usage
2026/01/27 by Mrinank Sharma, Miles McCain, Raymond Douglas +1 · 18 voices · 1 citation
#cs.CY #cs.AI #cs.CL #cs.HC
- Towards Understanding Linear Word Analogies
2018/10/11 by Kawin Ethayarajh, David Duvenaud, Ethayarajh, Kawin +3 · 1 voice · 7 citations
#cs.CL
- FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models
2018/10/02 by Will Grathwohl, Grathwohl, Will, Ricky T. Q. Chen +7 · 78 citations
Computer Science · Physics and Astronomy · #Generative Adversarial Networks and Image Synthesis #Model Reduction and Neural Networks #Computational Physics and Python Applications
- Getting to the Point. Index Sets and Parallelism-Preserving Autodiff for Pointful Array Programming
2021/04/12 by Adam Paszke, Daniel Johnson, Paszke, Adam +14 · 3 voices · 3 citations
Computer Science · #Cloud Computing and Resource Management #Logic, programming, and type systems #Parallel Computing and Optimization Techniques #cs.PL
- Convolutional Networks on Graphs for Learning Molecular Fingerprints
2015/09/30 by David Duvenaud, Duvenaud, David, Dougal Maclaurin +11 · 40 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Materials Science · #Computational Drug Discovery Methods #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Materials Science #Neural and Evolutionary Computing (cs.NE) #Protein Structure and Dynamics
- Learning Differential Equations that are Easy to Solve
2020/07/09 by Jacob Kelly, Kelly, Jacob, Jesse Bettencourt +6 · 2 voices · 4 citations
Physics and Astronomy · Computer Science · #cs.LG #stat.ML
- HMSPC: A Hybrid Mechanistic-Stochastic Physical-Continuous Model for Battery Dynamics
2019/07/08 by Yulia Rubanova, Rubanova, Yulia, Ricky T. Q. Chen +3 · 29 citations
Computer Science · Decision Sciences · Engineering · #Time Series Analysis and Forecasting #Stock Market Forecasting Methods #Energy Load and Power Forecasting
- Additive Gaussian Processes
2011/12/19 by David Duvenaud, Duvenaud, David, Hannes Nickisch +3 · 18 citations
Computer Science · #Gaussian Processes and Bayesian Inference #Machine Learning and Data Classification #Neural Networks and Applications
- Efficient Graph Generation with Graph Recurrent Attention Networks
2019/10/02 by Renjie Liao, Liao, Renjie, Yujia Li +14 · 26 citations
Computer Science · #Advanced Graph Neural Networks #Topic Modeling #Graph Theory and Algorithms
- Composing graphical models with neural networks for structured representations and fast inference
2016/03/20 by Matthew Johnson, Johnson, Matthew J., David Duvenaud +7 · 23 citations
Computer Science · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Neural Networks and Applications #Time Series Analysis and Forecasting
- Inference Suboptimality in Variational Autoencoders
2018/01/10 by Chris Cremer, Xuechen Li, Cremer, Chris +3 · 16 citations
Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks
- Backpropagation through the Void: Optimizing control variates for black-box gradient estimation
2017/10/31 by Will Grathwohl, Dami Choi, Grathwohl, Will +7 · 14 citations
Computer Science · Physics and Astronomy · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Reinforcement Learning in Robotics
- Probabilistic ODE Solvers with Runge-Kutta Means
2014/06/10 by Michael Schober, Schober, Michael, David Duvenaud +3 · 6 citations
Computer Science · Decision Sciences · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Numerical Analysis (math.NA) #Scientific Research and Discoveries #Simulation Techniques and Applications
- Explaining Image Classifiers by Counterfactual Generation
2018/07/20 by Chun‐Hao Chang, Chang, Chun-Hao, Elliot Creager +5 · 7 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · #Cell Image Analysis Techniques #Computer Vision and Pattern Recognition (cs.CV) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis
- Noisy Natural Gradient as Variational Inference
2017/12/06 by Guodong Zhang, Zhang, Guodong, Shengyang Sun +5 · 7 citations
Computer Science · #Machine Learning and Algorithms #Gaussian Processes and Bayesian Inference #Machine Learning and Data Classification
- Generating and designing DNA with deep generative models
2017/12/17 by Nathan Killoran, Leo J. Lee, Killoran, Nathan +7 · 5 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · #Evolutionary Algorithms and Applications #FOS: Biological sciences #FOS: Computer and information sciences #Genomics (q-bio.GN) #Genomics and Chromatin Dynamics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #RNA and protein synthesis mechanisms
- Tools for Verifying Neural Models' Training Data
2023/07/02 by Dami Choi, Yonadav Shavit, Choi, Dami +3 · 1 voice · 4 citations
#cs.LG #cs.CR
- A Study of Gradient Variance in Deep Learning
2020/07/09 by Fartash Faghri, Faghri, Fartash, David Duvenaud +5 · 4 citations
Computer Science · #Advanced Neural Network Applications #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Stochastic Gradient Optimization Techniques
- Understanding Undesirable Word Embedding Associations
2019/08/18 by Kawin Ethayarajh, Ethayarajh, Kawin, David Duvenaud +3 · 3 citations
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Hate Speech and Cyberbullying Detection #Natural Language Processing Techniques #Topic Modeling
- Experts Don't Cheat: Learning What You Don't Know By Predicting Pairs
2024/02/13 by Daniel D. Johnson, Daniel Tarlow, Johnson, Daniel D. +5 · 4 citations
Business, Management and Accounting · #Big Data and Business Intelligence
- The Artificial Self: Characterising the landscape of AI identity
2026/03/11 by Raymond Douglas, Jan Kulveit, Ondrej Havlicek +3 · 3 voices
Computer Science · #cs.AI
- Complex Momentum for Optimization in Games
2021/02/16 by Jonathan Lorraine, David Acuna, Lorraine, Jonathan +5 · 1 citation
Computer Science · Physics and Astronomy · #Adversarial Robustness in Machine Learning #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Model Reduction and Neural Networks