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Preetum Nakkiran

  1. Step-by-Step Diffusion: An Elementary Tutorial
    2024/06/13 by Preetum Nakkiran, Arwen Bradley, Nakkiran, Preetum +5 · 10 voices · 1 citation
    #cs.LG #cs.AI #cs.CV #stat.ML
  2. What Algorithms can Transformers Learn? A Study in Length Generalization
    2023/10/24 by Hattie Zhou, Arwen Bradley, Zhou, Hattie +13 · 2 voices · 21 citations
    Computer Science · #cs.LG #cs.AI #cs.CL #stat.ML
  3. Revisiting Model Stitching to Compare Neural Representations
    2021/06/14 by Yamini Bansal, Preetum Nakkiran, Bansal, Yamini +3 · 26 citations
    Computer Science · #Advanced Neural Network Applications #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Human Pose and Action Recognition #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  4. Normalizing Flows are Capable Generative Models
    2024/12/09 by Shuangfei Zhai, Zhai, Shuangfei, Ruixiang Zhang +18 · 2 voices · 34 citations
    Engineering · #Reservoir Engineering and Simulation Methods #cs.CV #cs.LG
  5. SGD on Neural Networks Learns Functions of Increasing Complexity
    2019/05/28 by Preetum Nakkiran, Gal Kaplun, Nakkiran, Preetum +11 · 18 citations
    Computer Science · Engineering · #Neural Networks and Applications #Machine Learning and Data Classification #Advanced Data Processing Techniques
  6. Optimal Regularization Can Mitigate Double Descent
    2020/03/04 by Preetum Nakkiran, Prayaag Venkat, Nakkiran, Preetum +5 · 8 citations
    Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural and Evolutionary Computing (cs.NE) #Sparse and Compressive Sensing Techniques #Statistics Theory (math.ST) #Stochastic Gradient Optimization Techniques
  7. Classifier-Free Guidance is a Predictor-Corrector
    2024/08/16 by Arwen Bradley, Preetum Nakkiran, Bradley, Arwen +1 · 14 citations
    Computer Science · #AI-based Problem Solving and Planning #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  8. LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures
    2023/12/07 by Vimal Thilak, Thilak, Vimal, Chen Huang +13 · 9 citations
    Computer Science · #Face and Expression Recognition #Machine Learning and Data Classification #Anomaly Detection Techniques and Applications
  9. Loss Minimization Yields Multicalibration for Large Neural Networks
    2023/04/19 by Jarosław Błasiok, Błasiok, Jarosław, Parikshit Gopalan +7 · 1 voice · 5 citations
    #cs.LG #cs.AI #stat.ML
  10. Vanishing Gradients in Reinforcement Finetuning of Language Models
    2023/10/31 by Noam Razin, Razin, Noam, Hattie Zhou +13 · 6 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Natural Language Processing Techniques #Reinforcement Learning in Robotics #Topic Modeling
  11. When Does Optimizing a Proper Loss Yield Calibration?
    2023/05/30 by Jarosław Błasiok, Błasiok, Jarosław, Parikshit Gopalan +5 · 6 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Statistics Theory (math.ST)
  12. Distributional Generalization: A New Kind of Generalization
    2020/09/17 by Preetum Nakkiran, Nakkiran, Preetum, Yamini Bansal +1 · 3 citations
    Computer Science · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification #Neural Networks and Applications #Neural and Evolutionary Computing (cs.NE) #Statistics Theory (math.ST)
  13. When is Multicalibration Post-Processing Necessary?
    2024/06/10 by Dutch Hansen, Hansen, Dutch, Siddartha Devic +5 · 1 voice · 5 citations
    Computer Science · Social Sciences · #Adversarial Robustness in Machine Learning #Ethics and Social Impacts of AI #Explainable Artificial Intelligence (XAI) #cs.LG
  14. How JEPA Avoids Noisy Features: The Implicit Bias of Deep Linear Self Distillation Networks
    2024/07/03 by Etai Littwin, Omid Saremi, Littwin, Etai +12 · 1 voice · 5 citations
    Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Neural Networks and Applications #cs.LG
  15. Limitations of the NTK for Understanding Generalization in Deep Learning
    2022/06/20 by Nikhil Vyas, Vyas, Nikhil, Yamini Bansal +3 · 2 citations
    Computer Science · Physics and Astronomy · #Neural Networks and Applications #Model Reduction and Neural Networks #Gaussian Processes and Bayesian Inference
  16. Composition and Control with Distilled Energy Diffusion Models and Sequential Monte Carlo
    2025/02/18 by James Thornton, Louis Béthune, Thornton, James +9 · 5 citations
    Computer Science · Engineering · Materials Science · #Advanced Control Systems Optimization #Advanced Mathematical Modeling in Engineering #Catalytic Processes in Materials Science #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  17. Perspectives on the State and Future of Deep Learning - 2023
    2023/12/07 by Micah Goldblum, Anima Anandkumar, Goldblum, Micah +17 · 3 voices
    #cs.AI #cs.LG
  18. Turing-Universal Learners with Optimal Scaling Laws
    2021/11/09 by Preetum Nakkiran, Nakkiran, Preetum · 1 citation
    Computer Science · #Algorithms and Data Compression #Artificial Intelligence (cs.AI) #Computability, Logic, AI Algorithms #Computational Complexity (cs.CC) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Statistics Theory (math.ST)
  19. APE: Aligning Pretrained Encoders to Quickly Learn Aligned Multimodal Representations
    2022/10/08 by Elan Rosenfeld, Rosenfeld, Elan, Preetum Nakkiran +7 · 1 citation
    Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Multimodal Machine Learning Applications
  20. Mechanisms of Projective Composition of Diffusion Models
    2025/02/06 by Arwen Bradley, Preetum Nakkiran, Bradley, Arwen +7 · 1 voice · 2 citations
    Computer Science · #Advanced Mathematical Modeling in Engineering
  21. Deconstructing Distributions: A Pointwise Framework of Learning
    2022/02/20 by Gal Kaplun, Nikhil Ghosh, Kaplun, Gal +7 · 1 citation
    Computer Science · #Machine Learning and Data Classification #Explainable Artificial Intelligence (XAI) #Adversarial Robustness in Machine Learning