Neural Processes

Follow this topic Ask about this topic

Momentum

2 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

Jul 13Week of Sep 28

Latest papers 46

All topics

Error- and Prediction-Driven Motor Learning in the Cortico-Cerebellar Loop
Sep 24, 2026Ana Carolina Filipe, Rui Ponte Costa, Cláudia SoaresRobotic Control Neural Processes
Department of Computer Science, NOVA School of Science and Technology, Caparica, Portugal · Centre for Neural Circuits and Behaviour, University of Oxford
NPBoost: Neural Processes with Gradient-Boosted Fixed Effects
Sep 23, 2026Andrea Nava, Ken Rölli, Armin Begic +1Meta-Learning Neural Processes
Seminar for Statistics, ETH Zurich, Switzerland · Lucerne University of Applied Sciences and Arts, Switzerland
Axonal delay dispersion decides whether a neuron detects an event or a sequence, and predicts cortical column diameter
Sep 3, 2026Cheng Bi, Jipeng SunNeural Processes Neural Encoding
Independent Researcher · Department of Computer Science, Princeton University
Stimulus-Evoked Network Dynamics in Human Cortical Organoids: From a Graph-Computational Framework to Repeated-Stimulation Depression
Jul 30, 2026Esmaeil S. Nadimi, Vinay C. Gogineni, Jan-Matthias Braun +3Neural Processes
Applied AI and Data Science Unit, Maersk Mc-Kinney Moller Institute, Faculty of Engineering, University of Southern Denmark · Biomedical Mass Spectrometry and System Biology Unit, Department of Biochemistry and Molecular Biology, Faculty of Science, University of Southern Denmark
Behaviour-Conditioned Neural Processes for Adaptive Residential Short-Term Load Forecasting
Jul 17, 2026Ramin Soleimani, Andrea Visentin, Dirk PeschNeural Processes Time Series Forecasting
School of Computer Science and Information Technology, University College Cork, Cork, Ireland
Human-AI Agent Interaction as a Neuroplastic Training Environment
Jul 14, 2026Eranga Bandara, Ross Gore, Asanga Gunaratna +17Neural Processes Human-AI Interaction
Old Dominion University, Norfolk, VA, USA · AI Motion Labs, Melbourne, Australia · Lithuanian University of Health Sciences +6
Neural Operator Processes for Probabilistic Operator Learning under Partial Observations
Jun 22, 2026Jose Miguel Lara-Rangel, Serge GuillasNeural Processes PDE Operator Learning
University College London London, United Kingdom
Machine Learning Methods for Studying Latent Neural Activity Dynamics
Jun 9, 2026Shufeng Kong, Fumei Deng, Xinyi Dong +7Dynamical Systems Latent Variable Models
School of Software Engineering, Sun Yat-sen University, Zhuhai, China · School of Computer Science and Artificial Intelligence, Foshan University, Foshan, China · Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA +2
Hyperbolic Neural Population Geometry Benefits Computation
Jun 8, 2026Dennis Wu, Yi-Chun Hung, Braden Yuille +2Neural Representation Geometry Neural Processes
Department of Computer Science, Northwestern University · Center for Foundation Models and Generative AI, Northwestern University · Integrated Science Program, Northwestern University +3
Revisiting Neural Processes via Fourier Transform and Volterra Series
May 31, 2026Peiman Mohseni, Nick Duffield, Raymond K. W. WongNeural Processes Frequency-Domain Feature Learning
Texas A&M University, College Station, Texas, USA.
Cortex and subcortex play distinct roles over learning when cortical memory is limited
May 30, 2026Matthew Farrell, Taro ToyoizumiComputational Cognitive Modeling Reinforcement Learning
Laboratory for Neural Computation and Adaptation RIKEN Center for Brain Science, Wako, Japan · Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan.
Supervised Training Rapidly Degrades Early Visual Cortex Alignment Across Biologically Plausible Learning Rules
May 28, 2026Nils LeuteneggerNeural Representation Geometry Predictive Coding
Independent Researcher, Switzerland
Misalignment Between Backpropagation and the Hierarchy of Brain Responses to Images
May 27, 2026Joséphine Raugel, Maximilian Seitzer, Marc Szafraniec +6Backpropagation Visual Representation Learning
Meta AI · Ecole Normale Supérieure, PSL University
Probabilistic Data-Driven Modelling of Astrophysical Transients: The Neural Process Family for Ultrafast and Class-Agnostic Light Curve Reconstruction with NightLANP
May 26, 2026Siddharth Chaini, Federica B. Bianco, Ashish MahabalIrregular Time-Series Modeling Neural Processes
Department of Physics and Astronomy, University of Delaware, Newark, DE 19716, USA · University of Delaware, Data Science Institute, Newark, DE 19716, USA · Joseph R. Biden, Jr. School of Public Policy and Administration, University of Delaware, DE 19716, USA +3
Metropolis-Scale Resilient and Trustworthy Traffic Flow Inference Using Multi-Source Data
May 24, 2026Qishen Zhou, Yifan Zhang, Michail A. Makridis +3Uncertainty Quantification Neural Processes
School of Transportation, Jilin University, Changchun, 130022, China · Department of Computer Science, City University of Hong Kong (Dongguan), Dongguan, 523808, China · Institute for Transport Planning and Systems, ETH Zurich, Zurich, 8093, Switzerland +2
Characterizing the Representational Capacity of Neural Processes
May 22, 2026Robin YoungNeural Processes Neural Network Expressivity
University of Cambridge
Learning dynamical systems with biochemically informed neural ordinary differential equations
May 22, 2026Luis L. Fonseca, Reinhard C. Laubenbacher, Lucas BöttcherDynamical Systems Neural Processes
Laboratory for Systems Medicine, Department of Medicine, University of Florida, Gainesville, FL, USA · Department of Computational Science and Philosophy, Frankfurt School of Finance and Management, Frankfurt am Main, 60322, Germany
Sparse Autoencoders Map Brain-LLM Alignment onto Cortical Semantic Topography
May 21, 2026Dongxin Guo, Jikun Wu, Siu Ming YiuNeural Processes LLM Interpretability
The University of Hong Kong · Hong Kong, China · Stellaris AI Limited
Cross-Species RSA Reveals Conserved Early Visual Alignment but Divergent Higher-Area Rankings Across Human fMRI and Macaque Electrophysiology
May 21, 2026Nils LeuteneggerRepresentational Similarity Analysis Visual Representation Learning
Independent Researcher, Switzerland
Temporal Coding as a Substrate for Sensorimotor Object Inference: A Spiking Reinterpretation of Thousand Brains Architecture
May 21, 2026Joy BoseNeural Processes Active Sensing
Independent Researcher, Bengaluru, India
Three Costs of Amortizing Gaussian Process Inference with Neural Processes
May 20, 2026Robin YoungLatent Variable Models Amortized Inference
University of Cambridge, Cambridge, UK
TIDE: Asymmetric Neural Circuits for Stabilized Temporal Inhibitory-Excitatory Dynamics
May 19, 2026Alexander Kyuroson, Denis Kleyko, Marcus LiwickiDynamic Neural Networks Neural Processes
Luleå University of Technology, Luleå, Sweden · Örebro University & RISE Research Institutes of Sweden
Efficient coding along the visual hierarchy
May 18, 2026Ananya Passi, Brian S. Robinson, Michael F. BonnerUnsupervised Learning Neural Processes
Department of Cognitive Science, Johns Hopkins University, Baltimore, MD, USA · Applied Physics Laboratory, Johns Hopkins University, Baltimore, MD, USA
Von Economo neurons enable reliable social skill acquisition in recurrent spiking neural networks: a computational account with clinical predictions
May 17, 2026Esila KeskinNeural Processes Recurrent Neural Networks
School of Computing and Creative Technologies, University of the West of England, Bristol, UK
Dual-axis attribution of zebrafish tectal microcircuits for energy-efficient and robust neurocomputing
May 13, 2026Ningping Li, Hao Zhang, Yi ZhouEfficient Neural Network Inference Neural Processes
University of Science and Technology of China, Hefei, China
Implicit Behavioral Decoding from Next-Step Spike Forecasts at Population Scale
May 13, 2026John R. Minnick, Jesus Gonzalez-Ferrer, Kamran Hussain +6Brain-Computer Interfaces Neural Processes
Department of Electrical and Computer Engineering, University of California, Santa Cruz, CA, USA · UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA · Department of Biomolecular Engineering, University of California, Santa Cruz, CA, USA +2
SpikeProphecy: A Large-Scale Benchmark for Autoregressive Neural Population Forecasting
May 13, 2026John R. Minnick, Jinghui Geng, Kamran Hussain +6Neural Processes Time Series Forecasting
Department of Electrical and Computer Engineering, University of California, Santa Cruz, CA, USA · UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA · Department of Computer Science and Engineering, University of California, Santa Cruz, CA, USA +2
Spectral Transformer Neural Processes
May 10, 2026Xianhe Chen, Hao Chen, Yingzhen LiTransformer Neural Processes
University of Cambridge · Tencent · Imperial College London
From Regression to Inference: Meta-Learning Predictors for Neural Architecture Search
May 10, 2026Liping Deng, MingQing XiaoNeural Surrogate Modeling Meta-Learning
Department of Mathematics University of California, Riverside Riverside, CA 92507 USA · School of Mathematical and Statistical Sciences Southern Illinois University Carbondale Carbondale, IL 62901 USA
PRIM: Meta-Learned Bayesian Root Cause Analysis
May 9, 2026Christopher Lohse, Anish Dhir, Amadou Ba +3Meta-Learning Neural Processes
University of Dublin, Trinity College, Dublin, Ireland · IBM · Gatsby Computational Neuroscience Unit, University College London +2

Sep 24, 2026, cs.LGJ/K move · Enter open · S save

Error- and Prediction-Driven Motor Learning in the Cortico-Cerebellar Loop

Ana Carolina Filipe, Rui Ponte Costa, Cláudia Soares

Department of Computer Science, NOVA School of Science and Technology, Caparica, Portugal · Centre for Neural Circuits and Behaviour, University of Oxford

Robotic Control Neural Processes Feedback Control

Open paper AskPDF arXiv

Robust control under delayed sensory feedback remains a key challenge in both robotics and neuroscience. Classical cerebellar models explain delay compensation through forward prediction but fail to account for fast online corrections and rapid adaptation observed in biological systems. We propose a cerebellum-inspired control framework that combines multiplexed predictive representations with internal feedback. By jointly encoding kinematic variables and task-relevant error signals, the model enables accurate online correction despite delayed feedback. Furthermore, incorporating feedback within the cerebellar loop significantly accelerates adaptation, reducing learning time by an order of magnitude. Our results show that single-signal predictions are insufficient under delay, while multiplexing and feedback together provide a unified mechanism for online control and rapid learning.

Momentum

Related topics

Latest papers 46