Frequency-Domain Feature Learning

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6 papers in the last four weeks, up 20% on the four weeks before. 0.1% of all new papers.

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Spectral Transformer Neural Processes
May 10, 2026Xianhe Chen, Hao Chen, Yingzhen LiTransformer Neural Processes
University of Cambridge · Tencent · Imperial College London
Hierarchical Multi-Scale Graph Neural Networks: Scalable Heterophilous Learning with Oversmoothing and Oversquashing Mitigation
May 8, 2026Md Sazzad Hossen, Avimanyu SahooGraph Neural Networks Over-Squashing
University of Alabama in Huntsville, Huntsville, AL, USA.
Preliminary Insights in Chronos Frequency Data Understanding and Reconstruction
May 7, 2026Alessandro Pagani, Marco Cominelli, Liying Han +11Frequency-Domain Feature Learning Time Series Representation Learning
DII, University of Brescia, Italy. · DEIB, Politecnico di Milano, Italy. · ECE Department, University of California, Los Angeles, USA. +6
Harmonized Feature Conditioning and Frequency-Prompt Personalization for Multi-Rater Medical Segmentation
May 6, 2026Sanaz Karimijafarbigloo, Armin Khosravi, Alireza Kheyrkhah +3Medical Image Analysis Frequency-Domain Feature Learning
Faculty of Informatics and Data Science, University of Regensburg, Regensburg, Germany · Sharif University of Technology, Tehran, Iran · Iran University of Science and Technology, Tehran, Iran +3
SpecPL: Disentangling Spectral Granularity for Prompt Learning
May 6, 2026Jingtao Zhou, Xirui Kang, Feiyang Huang +1VLM Adaptation Frequency-Domain Feature Learning
Department of Electrical Engineering, City University of Hong Kong, Hong Kong SAR.
Triple Spectral Fusion for Sensor-based Human Activity Recognition
May 4, 2026Ye Zhang, Longguang Wang, Qing Gao +3Graph Signal Processing Human Activity Recognition
School of Electronics and Communication Engineering, the Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, Shenzhen 518107, China · Aviation University of Air Force, Changchun 130012, China · College of Computer Science, Chongqing University, Chongqing 400044, China +1
RAFNet: Region-Aware Fusion Network for Pansharpening
May 4, 2026Jianing Zhang, Zijian Zhou, Kai SunDynamic Convolution Frequency-Domain Feature Learning
College of Artificial Intelligence, Xi’an Jiaotong University, Xi’an 710049, China · School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an 710049, China
Decompose to Understand, Fuse to Detect: Frequency-Decoupled Anomaly Detection for Encrypted Network Traffic
May 3, 2026Xinglin Lian, Chengtai Cao, Ting Zhong +3Frequency-Domain Feature Learning Network Intrusion Detection
School of Information and Software Engineering, University of Electronic Science and Technology of China · Department of Computer Science, City University of Hong Kong · Department of Computer Science and Engineering, Hong Kong University of Science and Technology +1
FEDIN: Frequency-Enhanced Deep Interest Network for Click-Through Rate Prediction
May 3, 2026Zenan Dai, Jinpeng Wang, Junwei Pan +3Sequential Recommendation Frequency-Domain Feature Learning
Tsinghua University Shenzhen, China · Harbin Institute of Technology, Shenzhen Shenzhen, China · Tencent Shenzhen, China
CGFformer: Cluster-Guidance Frequency Transformer for Pansharpening
May 2, 2026Zijian Zhou, Jianing Zhang, Kai Sun +3Frequency-Domain Feature Learning Remote Sensing
College of Artificial Intelligence, Xi’an Jiaotong University, Xi’an, 710049, China · School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, 710049, China · School of Computer Science and Technology, Xi’an Jiaotong University, Xi’an, 710049, China
PhaseNet++: Phase-Aware Frequency-Domain Anomaly Detection for Industrial Control Systems via Phase Coherence Graphs
Apr 30, 2026Raviteja Bommireddy, Varshith Bandaru, Lohith Pakala +1Cyber-Physical Systems Frequency-Domain Feature Learning
Department of CSE IIITDM Kancheepuram Chennai, India
Beyond the Baseband: Adaptive Multi-Band Encoding for Full-Spectrum Bioacoustics Classification
Apr 30, 2026Eklavya Sarkar, Marius Miron, David Robinson +6Audio Representation Learning Frequency-Domain Feature Learning
Earth Species Project
AdaMamba: Adaptive Frequency-Gated Mamba for Long-Term Time Series Forecasting
Apr 25, 2026Xudong Jiang, Mingshan Loo, Hanchen Yang +5Multivariate Time Series Forecasting Long-Term Time Series Forecasting
Tongji University Shanghai, China · Fudan University Shanghai, China
NAKUL-Med: Spectral-Graph State Space Models with Dynamics Kernels for Medical Signals
Apr 24, 2026Badri N. Patro, Vijay S. AgneeswaranElectroencephalography Neural Decoding
Microsoft
Unlocking Optical Prior: Spectrum-Guided Knowledge Transfer for SAR Generalized Category Discovery
Apr 24, 2026Jingyuan Xia, Ruikang Hu, Ye Li +3Domain Adaptation Frequency-Domain Feature Learning
College of Electronic Science and Technology, National University of Defense Technology, Changsha, 410073, China · State Key Laboratory of Complex System Simulation and Modeling Technology, Beijing, 100091, China
Convergent Evolution: How Different Language Models Learn Similar Number Representations
Apr 22, 2026Deqing Fu, Tianyi Zhou, Mikhail Belkin +2Fourier Feature Embeddings Frequency-Domain Feature Learning
University of Southern California · UC San Diego
Latent Fourier Transform
Apr 20, 2026Mason Wang, Cheng-Zhi Anna HuangControllable Music Generation Frequency-Domain Feature Learning
CSAIL
Exploring Boundary-Aware Spatial-Frequency Fusion for Camouflaged Object Detection
Apr 20, 2026Song Yu, Yang Hu, Haokang Ding +2Frequency-Domain Feature Learning Object Detection
School of Computer Science and Engineering, Central South University, Changsha, China
Unveiling Deepfakes: A Frequency-Aware Triple Branch Network for Deepfake Detection
Apr 19, 2026Qihao Shen, Jiaxing Xuan, Zhenguang Liu +5Frequency-Domain Feature Learning Deepfake Detection
State Key Laboratory of Blockchain and Data Security, Zhejiang University, Hangzhou, China · State Grid Blockchain Technology (Beijing) Co., Ltd., Beijing, China · Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security +3
Adaptive receptive field-based spatial-frequency feature reconstruction network for few-shot fine-grained image classification
Apr 18, 2026Linyue Zhang, Wenyi Zeng, Zicheng Pan +6Frequency-Domain Feature Learning Fine-Grained Image Classification
School of Electronic Information and Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an, Shaanxi Province, China · School of Electrical Engineering and Computer Science, the University of Queensland, QLD, Australia · Institute for Integrated and Intelligent Systems, Griffith University, QLD, Australia +4
Hybrid Spectro-Temporal Fusion Framework for Structural Health Monitoring
Apr 17, 2026Jongyeop Kim, Jinki Kim, Doyun LeeFrequency-Domain Feature Learning Multiscale Time-Series Modeling
aDepartment of Information Technology, Georgia Southern University Statesboro, GA, USA · bDepartment of Mechanical Engineering, Georgia Southern University Statesboro, GA, USA · cDepartment of Civil Engineering and Construction, Georgia Southern University Statesboro, GA, USA
Graph self-supervised learning based on frequency corruption
Apr 17, 2026Haojie Li, Mengjiao Zhang, Guanfeng Liu +3Graph Neural Networks Graph Representation Learning
School of Data Science, Qingdao University of Science and Technology Qingdao, China · School of Information Science and Technology, Qingdao University of Science and Technology Qingdao, China · School of Computing, Macquarie University Sydney, Australia
Frequency-Enhanced Dual-Subspace Networks for Few-Shot Fine-Grained Image Classification
Apr 16, 2026Meijia Wang, Guochao Wang, Haozhen Chu +4Frequency-Domain Feature Learning Fine-Grained Image Classification
School of Electronic Information and Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an 710000, China
FSDETR: Frequency-Spatial Feature Enhancement for Small Object Detection
Apr 16, 2026Jianchao Huang, Fengming Zhang, Haibo Zhu +1Frequency-Domain Feature Learning Small Object Detection
School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China
HAMSA: Scanning-Free Vision State Space Models via SpectralPulseNet
Apr 16, 2026Badri N. Patro, Vijay S. AgneeswaranFrequency-Domain Feature Learning Visual SSMs
Microsoft
FreqTrack: Frequency Learning based Vision Transformer for RGB-Event Object Tracking
Apr 16, 2026Jinlin You, Muyu Li, Xudong ZhaoVision Transformer Frequency-Domain Feature Learning
Dalian University of Technology
Frequency-aware decomposition learning for sensorless wrench estimation in vibration-rich robotic contact
Apr 14, 2026Hyeonbeen Lee, Min-Jae Jung, Tae-Kyeong Yeu +4Contact-Rich Robotic Manipulation Frequency-Domain Feature Learning
Department of Mechanical Engineering, Kyung Hee University, South Korea
FCL-COD: Weakly Supervised Camouflaged Object Detection with Frequency-aware and Contrastive Learning
Mar 24, 2026Jingchen Ni, Quan Zhang, Dan Jiang +3Contrastive Learning Frequency-Domain Feature Learning
Tsinghua University · Soochow University
FSCE: A Target-Aware Frequency-Spatial Collaborative Enhancement Framework for Noise-Resilient SAR ATR
Mar 23, 2026Yansong Lin, Zihan Cheng, Ziyue Yang +4Image Corruption Robustness Frequency-Domain Feature Learning
Laboratory of Intelligent Collaborative Computing, University of Electronic Science and Technology of China, China · School of Computer Science and Engineering (School of Artificial Intelligence), Wuhan Institute of Technology, China · Institute of Automation, Chinese Academy of Sciences, China +1
Dynamic High-frequency Convolution for Infrared Small Target Detection
Feb 3, 2026Ruojing Li, Chao Xiao, Qian Yin +5Dynamic Convolution Frequency-Domain Feature Learning
The authors are with the College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China.

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Spectral Transformer Neural Processes

Xianhe Chen, Hao Chen, Yingzhen Li

University of Cambridge · Tencent · Imperial College London

Transformer Neural Processes Frequency-Domain Feature Learning Time Series Forecasting Time Series Transformers

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Time series, spatial data, and images are natural applications of Neural Processes. However, when such data exhibit strong periodicity and quasi-periodicity, existing methods often suffer from underfitting and generalise poorly beyond the training distribution. In this work, we propose Spectral Transformer Neural Processes (STNPs), a frequency-aware extension of Transformer Neural Processes (TNPs). STNPs introduce a Spectral Aggregator that estimates an empirical context spectrum, compresses it into a spectral mixture, samples task-adaptive spectral features, and concatenates them with time-domain embeddings, thereby injecting a spectral-mixture-kernel bias into TNPs. This design reshapes the similarity geometry, allowing inputs that are distant in Euclidean space to remain close in an induced periodic manifold while enhancing time-frequency interactions. Extensive experiments on synthetic regression tasks, real-world time-series datasets, and an image dataset demonstrate that STNPs consistently improve predictive performance over existing baselines, extending Neural Processes beyond translation equivariance towards effective modelling of periodicity and quasi-periodicity.

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Latest papers 126