Cengiz Pehlevan

151 papers A* 42Misc 10Journal 91Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Random Matrix Theory Perspective on the Consistency of Diffusion Models. CoRR Binxu Wang, Jacob A. Zavatone-Veth, Cengiz Pehlevan
2026	J	`jnl`	Anytime Pretraining: Horizon-Free Learning-Rate Schedules with Weight Averaging. CoRR Alexandru Meterez, Pranav Ajit Nair, Depen Morwani, Cengiz Pehlevan, Sham M. Kakade
2026	J	`jnl`	Boule or Baguette? A Study on Task Topology, Length Generalization, and the Benefit of Reasoning Traces. CoRR William L. Tong, Ege Cakar, Cengiz Pehlevan
2026	J	`jnl`	Hyperparameter Transfer with Mixture-of-Expert Layers. CoRR Tianze Jiang, Blake Bordelon, Cengiz Pehlevan, Boris Hanin
2026	J	`jnl`	Jailbreak Scaling Laws for Large Language Models: Polynomial-Exponential Crossover. CoRR Indranil Halder, Annesya Banerjee, Cengiz Pehlevan
2026	J	`jnl`	Universal One-third Time Scaling in Learning Peaked Distributions. CoRR Yizhou Liu, Ziming Liu, Cengiz Pehlevan, Jeff Gore
2025	A*	`conf`	A Model of Place Field Reorganization During Reward Maximization. ICML M. Ganesh Kumar, Blake Bordelon, Jacob A. Zavatone-Veth, Cengiz Pehlevan
2025	J	`jnl`	A Simplified Analysis of SGD for Linear Regression with Weight Averaging. CoRR Alexandru Meterez, Depen Morwani, Costin-Andrei Oncescu, Jingfeng Wu, Cengiz Pehlevan, Sham M. Kakade
2025	J	`jnl`	A precise asymptotic analysis of learning diffusion models: theory and insights. CoRR Hugo Cui, Cengiz Pehlevan, Yue M. Lu
2025	A*	`conf`	Adaptive kernel predictors from feature-learning infinite limits of neural networks. ICML Clarissa Lauditi, Blake Bordelon, Cengiz Pehlevan
2025	J	`jnl`	Adaptive kernel predictors from feature-learning infinite limits of neural networks. CoRR Clarissa Lauditi, Blake Bordelon, Cengiz Pehlevan
2025	J	`jnl`	Convex Relaxation for Solving Large-Margin Classifiers in Hyperbolic Space. Trans. Mach. Learn. Res. Sheng Yang, Peihan Liu, Cengiz Pehlevan
2025	A*	`conf`	Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer. ICML Blake Bordelon, Cengiz Pehlevan
2025	J	`jnl`	Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer. CoRR Blake Bordelon, Cengiz Pehlevan
2025	J	`jnl`	Demystifying LLM-as-a-Judge: Analytically Tractable Model for Inference-Time Scaling. CoRR Indranil Halder, Cengiz Pehlevan
2025	J	`jnl`	Discovering alternative solutions beyond the simplicity bias in recurrent neural networks. CoRR William Qian, Cengiz Pehlevan
2025	A*	`conf`	Do Mice Grok? Glimpses of Hidden Progress in Sensory Cortex. ICLR Tanishq Kumar, Blake Bordelon, Cengiz Pehlevan, Venkatesh N. Murthy, Samuel J. Gershman
2025	J	`jnl`	Don't be lazy: CompleteP enables compute-efficient deep transformers. CoRR Nolan Dey, Bin Claire Zhang, Lorenzo Noci, Mufan Bill Li, Blake Bordelon, Shane Bergsma, Cengiz Pehlevan, Boris Hanin, Joel Hestness
2025	J	`jnl`	Echo Chamber: RL Post-training Amplifies Behaviors Learned in Pretraining. CoRR Rosie Zhao, Alexandru Meterez, Sham M. Kakade, Cengiz Pehlevan, Samy Jelassi, Eran Malach
2025	J	`jnl`	Error Broadcast and Decorrelation as a Potential Artificial and Natural Learning Mechanism. CoRR Mete Erdogan, Cengiz Pehlevan, Alper T. Erdogan
2025	A*	`conf`	How Feature Learning Can Improve Neural Scaling Laws. ICLR Blake Bordelon, Alexander B. Atanasov, Cengiz Pehlevan
2025	J	`jnl`	Learning richness modulates equality reasoning in neural networks. CoRR William L. Tong, Cengiz Pehlevan
2025	A*	`conf`	MLPs Learn In-Context on Regression and Classification Tasks. ICLR William Lingxiao Tong, Cengiz Pehlevan
2025	A*	`conf`	No Free Lunch from Random Feature Ensembles: Scaling Laws and Near-Optimality Conditions. ICML Benjamin S. Ruben, William Lingxiao Tong, Hamza Tahir Chaudhry, Cengiz Pehlevan
2025	—	`conf`	Pixel-Based Similarities as an Alternative to Neural Data for Improving Convolutional Neural Network Adversarial Robustness. IEEECONF Elie Attias, Cengiz Pehlevan, Dina Obeid
2025	J	`jnl`	Pretrain-Test Task Alignment Governs Generalization in In-Context Learning. CoRR Mary I. Letey, Jacob A. Zavatone-Veth, Yue M. Lu, Cengiz Pehlevan
2025	A*	`conf`	Risk and cross validation in ridge regression with correlated samples. ICML Alexander B. Atanasov, Jacob A. Zavatone-Veth, Cengiz Pehlevan
2025	A*	`conf`	Scaling Laws for Precision. ICLR Tanishq Kumar, Zachary Ankner, Benjamin Frederick Spector, Blake Bordelon, Niklas Muennighoff, Mansheej Paul, Cengiz Pehlevan, Christopher Ré, Aditi Raghunathan
2025	J	`jnl`	Seesaw: Accelerating Training by Balancing Learning Rate and Batch Size Scheduling. CoRR Alexandru Meterez, Depen Morwani, Jingfeng Wu, Costin-Andrei Oncescu, Cengiz Pehlevan, Sham M. Kakade
2025	—	`conf`	Spectral regularization for adversarially-robust representation learning. IEEECONF Sheng Yang, Jacob A. Zavatone-Veth, Cengiz Pehlevan
2025	A*	`conf`	The Optimization Landscape of SGD Across the Feature Learning Strength. ICLR Alexander B. Atanasov, Alexandru Meterez, James B. Simon, Cengiz Pehlevan
2025	J	`jnl`	Theory of Scaling Laws for In-Context Regression: Depth, Width, Context and Time. CoRR Blake Bordelon, Mary I. Letey, Cengiz Pehlevan
2025	J	`jnl`	Transfer Learning in Infinite Width Feature Learning Networks. CoRR Clarissa Lauditi, Blake Bordelon, Cengiz Pehlevan
2025	J	`jnl`	Two-Point Deterministic Equivalence for Stochastic Gradient Dynamics in Linear Models. CoRR Alexander B. Atanasov, Blake Bordelon, Jacob A. Zavatone-Veth, Courtney Paquette, Cengiz Pehlevan
2024	J	`jnl`	A Brain-Inspired Regularizer for Adversarial Robustness. CoRR Elie Attias, Cengiz Pehlevan, Dina Obeid
2024	A*	`conf`	A Dynamical Model of Neural Scaling Laws. ICML Blake Bordelon, Alexander B. Atanasov, Cengiz Pehlevan
2024	J	`jnl`	A Dynamical Model of Neural Scaling Laws. CoRR Blake Bordelon, Alexander B. Atanasov, Cengiz Pehlevan
2024	J	`jnl`	Asymptotic theory of in-context learning by linear attention. CoRR Yue M. Lu, Mary I. Letey, Jacob A. Zavatone-Veth, Anindita Maiti, Cengiz Pehlevan
2024	J	`jnl`	Convex Relaxation for Solving Large-Margin Classifiers in Hyperbolic Space. CoRR Sheng Yang, Peihan Liu, Cengiz Pehlevan
2024	A*	`conf`	Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit. ICLR Blake Bordelon, Lorenzo Noci, Mufan Bill Li, Boris Hanin, Cengiz Pehlevan
2024	J	`jnl`	Do Mice Grok? Glimpses of Hidden Progress During Overtraining in Sensory Cortex. CoRR Tanishq Kumar, Blake Bordelon, Cengiz Pehlevan, Venkatesh N. Murthy, Samuel J. Gershman
2024	A*	`conf`	Grokking as the transition from lazy to rich training dynamics. ICLR Tanishq Kumar, Blake Bordelon, Samuel J. Gershman, Cengiz Pehlevan
2024	J	`jnl`	How Feature Learning Can Improve Neural Scaling Laws. CoRR Blake Bordelon, Alexander B. Atanasov, Cengiz Pehlevan
2024	A*	`conf`	Infinite Limits of Multi-head Transformer Dynamics. NeurIPS Blake Bordelon, Hamza Tahir Chaudhry, Cengiz Pehlevan
2024	J	`jnl`	Infinite Limits of Multi-head Transformer Dynamics. CoRR Blake Bordelon, Hamza Tahir Chaudhry, Cengiz Pehlevan
2024	J	`jnl`	MLPs Learn In-Context. CoRR William L. Tong, Cengiz Pehlevan
2024	J	`jnl`	No Free Lunch From Random Feature Ensembles. CoRR Benjamin S. Ruben, William L. Tong, Hamza Tahir Chaudhry, Cengiz Pehlevan
2024	A*	`conf`	Partial observation can induce mechanistic mismatches in data-constrained models of neural dynamics. NeurIPS William Qian, Jacob A. Zavatone-Veth, Benjamin S. Ruben, Cengiz Pehlevan
2024	J	`jnl`	Risk and cross validation in ridge regression with correlated samples. CoRR Alexander B. Atanasov, Jacob A. Zavatone-Veth, Cengiz Pehlevan
2024	J	`jnl`	Scaling Laws for Precision. CoRR Tanishq Kumar, Zachary Ankner, Benjamin Spector, Blake Bordelon, Niklas Muennighoff, Mansheej Paul, Cengiz Pehlevan, Christopher Ré, Aditi Raghunathan
2024	J	`jnl`	Scaling and renormalization in high-dimensional regression. CoRR Alexander B. Atanasov, Jacob A. Zavatone-Veth, Cengiz Pehlevan
2024	J	`jnl`	Spectral regularization for adversarially-robust representation learning. CoRR Sheng Yang, Jacob A. Zavatone-Veth, Cengiz Pehlevan
2024	J	`jnl`	The Optimization Landscape of SGD Across the Feature Learning Strength. CoRR Alexander B. Atanasov, Alexandru Meterez, James B. Simon, Cengiz Pehlevan
2023	J	`jnl`	Bandwidth Enables Generalization in Quantum Kernel Models. Trans. Mach. Learn. Res. Abdulkadir Canatar, Evan Peters, Cengiz Pehlevan, Stefan M. Wild, Ruslan Shaydulin
2023	A*	`conf`	Correlative Information Maximization Based Biologically Plausible Neural Networks for Correlated Source Separation. ICLR Bariscan Bozkurt, Ates Isfendiyaroglu, Cengiz Pehlevan, Alper Tunga Erdogan
2023	A*	`conf`	Correlative Information Maximization: A Biologically Plausible Approach to Supervised Deep Neural Networks without Weight Symmetry. NeurIPS Bariscan Bozkurt, Cengiz Pehlevan, Alper T. Erdogan
2023	J	`jnl`	Correlative Information Maximization: A Biologically Plausible Approach to Supervised Deep Neural Networks without Weight Symmetry. CoRR Bariscan Bozkurt, Cengiz Pehlevan, Alper T. Erdogan
2023	J	`jnl`	Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit. CoRR Blake Bordelon, Lorenzo Noci, Mufan Bill Li, Boris Hanin, Cengiz Pehlevan
2023	A*	`conf`	Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks. NeurIPS Blake Bordelon, Cengiz Pehlevan
2023	J	`jnl`	Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks. CoRR Blake Bordelon, Cengiz Pehlevan
2023	J	`jnl`	Dynamics of Temporal Difference Reinforcement Learning. CoRR Blake Bordelon, Paul Masset, Henry Kuo, Cengiz Pehlevan
2023	A*	`conf`	Feature-Learning Networks Are Consistent Across Widths At Realistic Scales. NeurIPS Nikhil Vyas, Alexander B. Atanasov, Blake Bordelon, Depen Morwani, Sabarish Sainathan, Cengiz Pehlevan
2023	J	`jnl`	Feature-Learning Networks Are Consistent Across Widths At Realistic Scales. CoRR Nikhil Vyas, Alexander B. Atanasov, Blake Bordelon, Depen Morwani, Sabarish Sainathan, Cengiz Pehlevan
2023	J	`jnl`	Grokking as the Transition from Lazy to Rich Training Dynamics. CoRR Tanishq Kumar, Blake Bordelon, Samuel J. Gershman, Cengiz Pehlevan
2023	A*	`conf`	Interneurons accelerate learning dynamics in recurrent neural networks for statistical adaptation. ICLR David Lipshutz, Cengiz Pehlevan, Dmitri B. Chklovskii
2023	A*	`conf`	Learning Curves for Deep Structured Gaussian Feature Models. NeurIPS Jacob A. Zavatone-Veth, Cengiz Pehlevan
2023	J	`jnl`	Learning Curves for Heterogeneous Feature-Subsampled Ridge Ensembles. CoRR Benjamin S. Ruben, Cengiz Pehlevan
2023	A*	`conf`	Learning Curves for Noisy Heterogeneous Feature-Subsampled Ridge Ensembles. NeurIPS Benjamin S. Ruben, Cengiz Pehlevan
2023	J	`jnl`	Learning curves for deep structured Gaussian feature models. CoRR Jacob A. Zavatone-Veth, Cengiz Pehlevan
2023	A*	`conf`	Long Sequence Hopfield Memory. NeurIPS Hamza Tahir Chaudhry, Jacob A. Zavatone-Veth, Dmitry Krotov, Cengiz Pehlevan
2023	J	`jnl`	Long Sequence Hopfield Memory. CoRR Hamza Tahir Chaudhry, Jacob A. Zavatone-Veth, Dmitry Krotov, Cengiz Pehlevan
2023	A*	`conf`	Loss Dynamics of Temporal Difference Reinforcement Learning. NeurIPS Blake Bordelon, Paul Masset, Henry Kuo, Cengiz Pehlevan
2023	A*	`conf`	Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb. NeurIPS Jacob A. Zavatone-Veth, Paul Masset, William L. Tong, Joseph D. Zak, Venkatesh Murthy, Cengiz Pehlevan
2023	J	`jnl`	Neural networks learn to magnify areas near decision boundaries. CoRR Jacob A. Zavatone-Veth, Sheng Yang, Julian A. Rubinfien, Cengiz Pehlevan
2023	A*	`conf`	The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks. ICLR Blake Bordelon, Cengiz Pehlevan
2023	A*	`conf`	The Onset of Variance-Limited Behavior for Networks in the Lazy and Rich Regimes. ICLR Alexander B. Atanasov, Blake Bordelon, Sabarish Sainathan, Cengiz Pehlevan
2022	—	`conf`	A Kernel Analysis of Feature Learning in Deep Neural Networks. Allerton Abdulkadir Canatar, Cengiz Pehlevan
2022	J	`jnl`	Bandwidth Enables Generalization in Quantum Kernel Models. CoRR Abdulkadir Canatar, Evan Peters, Cengiz Pehlevan, Stefan M. Wild, Ruslan Shaydulin
2022	J	`jnl`	Biologically plausible single-layer networks for nonnegative independent component analysis. Biol. Cybern. David Lipshutz, Cengiz Pehlevan, Dmitri B. Chklovskii
2022	A*	`conf`	Biologically-Plausible Determinant Maximization Neural Networks for Blind Separation of Correlated Sources. NeurIPS Bariscan Bozkurt, Cengiz Pehlevan, Alper T. Erdogan
2022	J	`jnl`	Biologically-Plausible Determinant Maximization Neural Networks for Blind Separation of Correlated Sources. CoRR Bariscan Bozkurt, Cengiz Pehlevan, Alper T. Erdogan
2022	A*	`conf`	Capacity of Group-invariant Linear Readouts from Equivariant Representations: How Many Objects can be Linearly Classified Under All Possible Views? ICLR Matthew Farrell, Blake Bordelon, Shubhendu Trivedi, Cengiz Pehlevan
2022	J	`jnl`	Contrasting random and learned features in deep Bayesian linear regression. CoRR Jacob A. Zavatone-Veth, William L. Tong, Cengiz Pehlevan
2022	J	`jnl`	Correlative Information Maximization Based Biologically Plausible Neural Networks for Correlated Source Separation. CoRR Bariscan Bozkurt, Ates Isfendiyaroglu, Cengiz Pehlevan, Alper T. Erdogan
2022	J	`jnl`	Interneurons accelerate learning dynamics in recurrent neural networks for statistical adaptation. CoRR David Lipshutz, Cengiz Pehlevan, Dmitri B. Chklovskii
2022	A*	`conf`	Learning Curves for SGD on Structured Features. ICLR Blake Bordelon, Cengiz Pehlevan
2022	A*	`conf`	Natural gradient enables fast sampling in spiking neural networks. NeurIPS Paul Masset, Jacob A. Zavatone-Veth, J. Patrick Connor, Venkatesh Murthy, Cengiz Pehlevan
2022	A*	`conf`	Neural Networks as Kernel Learners: The Silent Alignment Effect. ICLR Alexander B. Atanasov, Blake Bordelon, Cengiz Pehlevan
2022	J	`jnl`	On Neural Network Kernels and the Storage Capacity Problem. Neural Comput. Jacob A. Zavatone-Veth, Cengiz Pehlevan
2022	J	`jnl`	On neural network kernels and the storage capacity problem. CoRR Jacob A. Zavatone-Veth, Cengiz Pehlevan
2022	A*	`conf`	Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks. NeurIPS Blake Bordelon, Cengiz Pehlevan
2022	J	`jnl`	Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks. CoRR Blake Bordelon, Cengiz Pehlevan
2022	J	`jnl`	The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks. CoRR Blake Bordelon, Cengiz Pehlevan
2022	J	`jnl`	The Onset of Variance-Limited Behavior for Networks in the Lazy and Rich Regimes. CoRR Alexander B. Atanasov, Blake Bordelon, Sabarish Sainathan, Cengiz Pehlevan
2021	A*	`conf`	Asymptotics of representation learning in finite Bayesian neural networks. NeurIPS Jacob A. Zavatone-Veth, Abdulkadir Canatar, Benjamin S. Ruben, Cengiz Pehlevan
2021	J	`jnl`	Asymptotics of representation learning in finite Bayesian neural networks. CoRR Jacob A. Zavatone-Veth, Abdulkadir Canatar, Cengiz Pehlevan
2021	A*	`conf`	Attention Approximates Sparse Distributed Memory. NeurIPS Trenton Bricken, Cengiz Pehlevan
2021	J	`jnl`	Attention Approximates Sparse Distributed Memory. CoRR Trenton Bricken, Cengiz Pehlevan
2021	J	`jnl`	Capacity of Group-invariant Linear Readouts from Equivariant Representations: How Many Objects can be Linearly Classified Under All Possible Views? CoRR Matthew Farrell, Blake Bordelon, Shubhendu Trivedi, Cengiz Pehlevan
2021	J	`jnl`	Contrastive Similarity Matching for Supervised Learning. Neural Comput. Shanshan Qin, Nayantara Mudur, Cengiz Pehlevan
2021	—	`conf`	Depth induces scale-averaging in overparameterized linear Bayesian neural networks. ACSCC Jacob A. Zavatone-Veth, Cengiz Pehlevan
2021	J	`jnl`	Depth induces scale-averaging in overparameterized linear Bayesian neural networks. CoRR Jacob A. Zavatone-Veth, Cengiz Pehlevan
2021	A*	`conf`	Exact marginal prior distributions of finite Bayesian neural networks. NeurIPS Jacob A. Zavatone-Veth, Cengiz Pehlevan
2021	J	`jnl`	Exact priors of finite neural networks. CoRR Jacob A. Zavatone-Veth, Cengiz Pehlevan
2021	J	`jnl`	Learning Curves for SGD on Structured Features. CoRR Blake Bordelon, Cengiz Pehlevan
2021	J	`jnl`	Neural Networks as Kernel Learners: The Silent Alignment Effect. CoRR Alexander B. Atanasov, Blake Bordelon, Cengiz Pehlevan
2021	A*	`conf`	Out-of-Distribution Generalization in Kernel Regression. NeurIPS Abdulkadir Canatar, Blake Bordelon, Cengiz Pehlevan
2021	J	`jnl`	Out-of-Distribution Generalization in Kernel Regression. CoRR Abdulkadir Canatar, Blake Bordelon, Cengiz Pehlevan
2020	J	`jnl`	Activation function dependence of the storage capacity of treelike neural networks. CoRR Jacob A. Zavatone-Veth, Cengiz Pehlevan
2020	A*	`conf`	Associative Memory in Iterated Overparameterized Sigmoid Autoencoders. ICML Yibo Jiang, Cengiz Pehlevan
2020	J	`jnl`	Associative Memory in Iterated Overparameterized Sigmoid Autoencoders. CoRR Yibo Jiang, Cengiz Pehlevan
2020	Misc	`conf`	Blind Bounded Source Separation Using Neural Networks with Local Learning Rules. ICASSP Alper T. Erdogan, Cengiz Pehlevan
2020	J	`jnl`	Blind Bounded Source Separation Using Neural Networks with Local Learning Rules. CoRR Alper T. Erdogan, Cengiz Pehlevan
2020	A*	`conf`	Minimax Dynamics of Optimally Balanced Spiking Networks of Excitatory and Inhibitory Neurons. NeurIPS Qianyi Li, Cengiz Pehlevan
2020	J	`jnl`	Neurons as Canonical Correlation Analyzers. Frontiers Comput. Neurosci. Cengiz Pehlevan, Xinyuan Zhao, Anirvan M. Sengupta, Dmitri B. Chklovskii
2020	A*	`conf`	Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks. ICML Blake Bordelon, Abdulkadir Canatar, Cengiz Pehlevan
2020	J	`jnl`	Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks. CoRR Blake Bordelon, Abdulkadir Canatar, Cengiz Pehlevan
2020	J	`jnl`	Statistical Mechanics of Generalization in Kernel Regression. CoRR Abdulkadir Canatar, Blake Bordelon, Cengiz Pehlevan
2020	J	`jnl`	Supervised Deep Similarity Matching. CoRR Shanshan Qin, Nayantara Mudur, Cengiz Pehlevan
2019	Misc	`conf`	A Closer Look at Disentangling in β-VAE. ACSSC Harshvardhan Sikka, Weishun Zhong, Jun Yin, Cengiz Pehlevan
2019	J	`jnl`	A Closer Look at Disentangling in β-VAE. CoRR Harshvardhan Sikka, Weishun Zhong, Jun Yin, Cengiz Pehlevan
2019	J	`jnl`	A Spiking Neural Network with Local Learning Rules Derived From Nonnegative Similarity Matching. CoRR Cengiz Pehlevan
2019	Misc	`conf`	A Spiking Neural Network with Local Learning Rules Derived from Nonnegative Similarity Matching. ICASSP Cengiz Pehlevan
2019	J	`jnl`	Neuroscience-Inspired Online Unsupervised Learning Algorithms: Artificial neural networks. IEEE Signal Process. Mag. Cengiz Pehlevan, Dmitri B. Chklovskii
2019	J	`jnl`	Neuroscience-inspired online unsupervised learning algorithms. CoRR Cengiz Pehlevan, Dmitri B. Chklovskii
2019	A*	`conf`	Structured and Deep Similarity Matching via Structured and Deep Hebbian Networks. NeurIPS Dina Obeid, Hugo Ramambason, Cengiz Pehlevan
2019	J	`jnl`	Structured and Deep Similarity Matching via Structured and Deep Hebbian Networks. CoRR Dina Obeid, Hugo Ramambason, Cengiz Pehlevan
2018	Misc	`conf`	Biologically Plausible Online Principal Component Analysis Without Recurrent Neural Dynamics. ACSSC Victor Minden, Cengiz Pehlevan, Dmitri B. Chklovskii
2018	—	`conf`	Efficient Principal Subspace Projection of Streaming Data Through Fast Similarity Matching. IEEE BigData Andrea Giovannucci, Victor Minden, Cengiz Pehlevan, Dmitri B. Chklovskii
2018	J	`jnl`	Efficient Principal Subspace Projection of Streaming Data Through Fast Similarity Matching. CoRR Andrea Giovannucci, Victor Minden, Cengiz Pehlevan, Dmitri B. Chklovskii
2018	A*	`conf`	Manifold-tiling Localized Receptive Fields are Optimal in Similarity-preserving Neural Networks. NeurIPS Anirvan M. Sengupta, Cengiz Pehlevan, Mariano Tepper, Alexander Genkin, Dmitri B. Chklovskii
2018	J	`jnl`	Why Do Similarity Matching Objectives Lead to Hebbian/Anti-Hebbian Networks? Neural Comput. Cengiz Pehlevan, Anirvan M. Sengupta, Dmitri B. Chklovskii
2017	Misc	`conf`	A clustering neural network model of insect olfaction. ACSSC Cengiz Pehlevan, Alexander Genkin, Dmitri B. Chklovskii
2017	J	`jnl`	Adversarial synapses: Hebbian/anti-Hebbian learning optimizes min-max objectives. CoRR Cengiz Pehlevan, Anirvan M. Sengupta, Dmitri B. Chklovskii
2017	J	`jnl`	Blind Nonnegative Source Separation Using Biological Neural Networks. Neural Comput. Cengiz Pehlevan, Sreyas Mohan, Dmitri B. Chklovskii
2017	J	`jnl`	Blind nonnegative source separation using biological neural networks. CoRR Cengiz Pehlevan, Sreyas Mohan, Dmitri B. Chklovskii
2017	—	`conf`	Resource-efficient perceptron has sparse synaptic weight distribution. SIU Cengiz Pehlevan, Anirvan M. Sengupta
2016	Misc	`conf`	Do retinal ganglion cells project natural scenes to their principal subspace and whiten them? ACSSC Reza Abbasi-Asl, Cengiz Pehlevan, Bin Yu, Dmitri B. Chklovskii
2016	J	`jnl`	Self-calibrating Neural Networks for Dimensionality Reduction. CoRR Yuansi Chen, Cengiz Pehlevan, Dmitri B. Chklovskii
2016	Misc	`conf`	Self-calibrating neural networks for dimensionality reduction. ACSSC Yuansi Chen, Cengiz Pehlevan, Dmitri B. Chklovskii
2015	J	`jnl`	A Hebbian/Anti-Hebbian Network Derived from Online Non-Negative Matrix Factorization Can Cluster and Discover Sparse Features. CoRR Cengiz Pehlevan, Dmitri B. Chklovskii
2015	J	`jnl`	A Hebbian/Anti-Hebbian Network for Online Sparse Dictionary Learning Derived from Symmetric Matrix Factorization. CoRR Tao Hu, Cengiz Pehlevan, Dmitri B. Chklovskii
2015	J	`jnl`	A Hebbian/Anti-Hebbian Neural Network for Linear Subspace Learning: A Derivation from Multidimensional Scaling of Streaming Data. CoRR Cengiz Pehlevan, Tao Hu, Dmitri B. Chklovskii
2015	J	`jnl`	A Hebbian/Anti-Hebbian Neural Network for Linear Subspace Learning: A Derivation from Multidimensional Scaling of Streaming Data. Neural Comput. Cengiz Pehlevan, Tao Hu, Dmitri B. Chklovskii
2015	—	`conf`	A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks. NIPS Cengiz Pehlevan, Dmitri B. Chklovskii
2015	J	`jnl`	A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks. CoRR Cengiz Pehlevan, Dmitri B. Chklovskii
2015	—	`conf`	Optimization theory of Hebbian/anti-Hebbian networks for PCA and whitening. Allerton Cengiz Pehlevan, Dmitri B. Chklovskii
2015	J	`jnl`	Optimization theory of Hebbian/anti-Hebbian networks for PCA and whitening. CoRR Cengiz Pehlevan, Dmitri B. Chklovskii
2014	Misc	`conf`	A Hebbian/Anti-Hebbian network derived from online non-negative matrix factorization can cluster and discover sparse features. ACSSC Cengiz Pehlevan, Dmitri B. Chklovskii
2014	Misc	`conf`	A Hebbian/Anti-Hebbian network for online sparse dictionary learning derived from symmetric matrix factorization. ACSSC Tao Hu, Cengiz Pehlevan, Dmitri B. Chklovskii
2013	Misc	`conf`	A neuron as a signal processing device. ACSSC Tao Hu, Zaid J. Towfic, Cengiz Pehlevan, Alex V. Genkin, Dmitri B. Chklovskii