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Blake Bordelon

  1. There Will Be a Scientific Theory of Deep Learning
    2026/04/23 by Jamie Simon, Daniel Kunin, Alexander Atanasov +11 · 31 voices · 1 citation
    #stat.ML #cs.LG
  2. Scaling Laws for Precision
    2024/11/07 by Tanishq Kumar, Zachary Ankner, Kumar, Tanishq +16 · 7 voices · 29 citations
    Arts and Humanities · #Philosophy and History of Science
  3. Don't be lazy: CompleteP enables compute-efficient deep transformers
    2025/05/02 by Bin Zhang, Dey, Nolan, Zhang, Bin Claire +14 · 1 voice · 20 citations
    Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Neural Networks and Applications #Parallel Computing and Optimization Techniques
  4. A Dynamical Model of Neural Scaling Laws
    2024/02/02 by Blake Bordelon, Alexander Atanasov, Bordelon, Blake +3 · 20 citations
    Neuroscience · Computer Science · #Neural dynamics and brain function #Neural Networks and Applications
  5. Grokking as the Transition from Lazy to Rich Training Dynamics
    2023/10/09 by Tanishq Kumar, Blake Bordelon, Kumar, Tanishq +5 · 12 citations
    Computer Science · Physics and Astronomy · #Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Reservoir Computing #Quantum many-body systems #Stochastic Gradient Optimization Techniques
  6. Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks
    2022/05/19 by Blake Bordelon, Cengiz Pehlevan, Bordelon, Blake +1 · 10 citations
    Computer Science · Physics and Astronomy · #Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Quantum many-body systems #Stochastic Gradient Optimization Techniques
  7. Feature-Learning Networks Are Consistent Across Widths At Realistic Scales
    2023/05/28 by Nikhil Vyas, Vyas, Nikhil, Alexander Atanasov +9 · 9 citations
    Computer Science · Materials Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning in Materials Science #Neural Networks and Applications #Stochastic Gradient Optimization Techniques
  8. Infinite Limits of Multi-head Transformer Dynamics
    2024/05/24 by Blake Bordelon, Hamza Tahir Chaudhry, Bordelon, Blake +3 · 1 voice · 9 citations
    Engineering · #Control and Stability of Dynamical Systems #Control Systems in Engineering #Physics and Engineering Research Articles
  9. Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit
    2023/09/28 by Blake Bordelon, Lorenzo Noci, Bordelon, Blake +7 · 9 citations
    Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #Artificial Intelligence (cs.AI) #Cell Image Analysis Techniques #Disordered Systems and Neural Networks (cond-mat.dis-nn) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks
  10. How Feature Learning Can Improve Neural Scaling Laws
    2024/09/26 by Blake Bordelon, Bordelon, Blake, Alexander Atanasov +3 · 12 citations
    Computer Science · #Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications
  11. Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer
    2025/02/04 by Blake Bordelon, Cengiz Pehlevan, Bordelon, Blake +1 · 6 citations
    Computer Science · #Neural Networks and Applications
  12. The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks
    2022/10/05 by Blake Bordelon, Cengiz Pehlevan, Bordelon, Blake +1 · 1 citation
    Computer Science · Neuroscience · Engineering · #Neural Networks and Applications #Neural dynamics and brain function #Advanced Memory and Neural Computing
  13. A Model of Place Field Reorganization During Reward Maximization
    2024/12/16 by M Ganeshkumar, Blake Bordelon, Jacob A. Zavatone-Veth +1 · 1 voice · 1 citation
    Neuroscience · #Memory and Neural Mechanisms #Neural dynamics and brain function #Neural and Behavioral Psychology Studies