Eric Nalisnick
- Normalizing Flows for Probabilistic Modeling and Inference
2019/12/05 by George Papamakarios, Eric Nalisnick, Danilo Jimenez Rezende +2 · 1 voice · 104 citations
#stat.ML #cs.LG
- Do Deep Generative Models Know What They Don't Know?
2018/10/22 by Eric Nalisnick, Akihiro Matsukawa, Nalisnick, Eric +8 · 1 voice · 29 citations
Computer Science · #Advanced Image and Video Retrieval Techniques #Advanced Neural Network Applications #Generative Adversarial Networks and Image Synthesis #cs.LG #stat.ML
- Do Bayesian Neural Networks Need To Be Fully Stochastic?
2022/11/11 by Mrinank Sharma, Sharma, Mrinank, Sebastian Farquhar +5 · 1 voice · 8 citations
Computer Science · Mathematics · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #cs.AI #cs.LG #stat.ML
- Bayesian Deep Learning via Subnetwork Inference
2020/10/28 by Erik Daxberger, Daxberger, Erik, Eric Nalisnick +7 · 11 citations
Computer Science · #Gaussian Processes and Bayesian Inference #Adversarial Robustness in Machine Learning #Machine Learning and Data Classification
- Learning to Defer to Multiple Experts: Consistent Surrogate Losses, Confidence Calibration, and Conformal Ensembles
2022/10/30 by Rajeev Verma, Verma, Rajeev, Daniel Barrejón +3 · 9 citations
Computer Science · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
- Bayesian Batch Active Learning as Sparse Subset Approximation
2019/08/06 by Robert Pinsler, Pinsler, Robert, Jonathan Gordon +5 · 5 citations
Computer Science · #Machine Learning and Algorithms #Gaussian Processes and Bayesian Inference #Algorithms and Data Compression
- On the Challenges and Opportunities in Generative AI
2024/02/28 by Laura Manduchi, Manduchi, Laura, Kushagra Pandey +48 · 7 citations
Computer Science · #AI-based Problem Solving and Planning #Cognitive Computing and Networks #Evolutionary Algorithms and Applications
- Learning to Defer to a Population: A Meta-Learning Approach
2024/03/05 by Dharmesh Tailor, Aditya Kumar Patra, Tailor, Dharmesh +7 · 5 citations
Computer Science · #Machine Learning and Data Classification
- Hate Speech Criteria: A Modular Approach to Task-Specific Hate Speech Definitions
2022/06/30 by Urja Khurana, Khurana, Urja, Ivar Vermeulen +7 · 2 citations
Computer Science · #Hate Speech and Cyberbullying Detection
- A Scale Mixture Perspective of Multiplicative Noise in Neural Networks
2015/06/10 by Eric Nalisnick, Anima Anandkumar, Nalisnick, Eric +3 · 1 citation
Computer Science · #Gaussian Processes and Bayesian Inference #Neural Networks and Applications #Generative Adversarial Networks and Image Synthesis
- Exploiting Inferential Structure in Neural Processes
2023/06/27 by Dharmesh Tailor, Mohammad Emtiyaz Khan, Tailor, Dharmesh +3 · 1 citation
Computer Science · Materials Science · Physics and Astronomy · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Materials Science #Model Reduction and Neural Networks #Neural Networks and Applications
- Uncertainty Aware Tropical Cyclone Wind Speed Estimation from Satellite Data
2024/04/12 by Nils Lehmann, Lehmann, Nils, Nina Maria Gottschling +5 · 1 citation
Earth and Planetary Sciences · Engineering · #Tropical and Extratropical Cyclones Research #Ocean Waves and Remote Sensing #Synthetic Aperture Radar (SAR) Applications and Techniques
- Crowd-Calibrator: Can Annotator Disagreement Inform Calibration in Subjective Tasks?
2024/08/26 by Urja Khurana, Eric Nalisnick, Khurana, Urja +5 · 1 citation
Social Sciences · #Misinformation and Its Impacts
- Controlling the Risk of Corrupted Contexts for Language Models via Early-Exiting
2025/10/02 by Metod Jazbec, Wynn, Andrea, Charith Peris +10 · 1 citation
Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multimodal Machine Learning Applications #Natural Language Processing Techniques #Topic Modeling