April 02, 2020 preprint Open access Predicting the outputs of finite deep neural networks trained with noisy gradients arXiv (Cornell University) DOI: 10.1103/physreve.104.064301 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 4 stored of 23 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Field theory for optimal signal propagation in residual networks 2025 Physical review. E article Computer Science Neural Networks and Applications Open access 0 citations Data variability in neural network Bayesian inference 2025 Physical Review Research article Computer Science Gaussian Processes and Bayesian Inference Open access 0 citations Decomposing neural networks as mappings of correlation functions 2022 Physical Review Research article Computer Science Neural Networks and Applications Open access 12 citations Unified field theoretical approach to deep and recurrent neuronal networks 2022 Journal of Statistical Mechanics Theory and Experiment article Computer Science Gaussian Processes and Bayesian Inference Open access 17 citations 4 results References 0