Frequency-Guided Deformable Networks for Continuous Phase Alignment | Paper Citation Record

Observation 9ed2684c-a8cb-44b5-8c8c-a8592aa6e5dc · outbound

This paper cites Foundation models for time series analysis: A tutorial and survey.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Foundation models for time series analysis: A tutorial and survey

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This paper cites Rethinking the role of llms in time series forecasting.arXiv preprint arXiv:2602.14744, 2026.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Rethinking the role of llms in time series forecasting.arXiv preprint arXiv:2602.14744, 2026

Reference 2

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This paper cites Timexer: Empowering transformers for time series forecasting with exogenous variables.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Timexer: Empowering transformers for time series forecasting with exogenous variables

Reference 3

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This paper cites Times- net: Temporal 2d-variation modeling for general time series analysis.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Times- net: Temporal 2d-variation modeling for general time series analysis

Reference 4

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Observation 06b9bb42-5c0d-4a81-bfc1-a9e6103d5221 · outbound

This paper cites Themis: Unlocking pretrained knowledge with foundation model embeddings for anomaly detection in time series.arXiv e-prints, pages arXiv–2510, 2025.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Themis: Unlocking pretrained knowledge with foundation model embeddings for anomaly detection in time series.arXiv e-prints, pages arXiv–2510, 2025

Reference 5

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Observation 619061aa-59b8-44d8-8698-933096808a88 · outbound

This paper cites A survey of network anomaly detection techniques.Journal of network and computer applications, 60:19–31, 2016.

Frequency-Guided Deformable Networks for Continuous Phase Alignment A survey of network anomaly detection techniques.Journal of network and computer applications, 60:19–31, 2016

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Observation c9de7244-6ee6-4a8f-9ec7-605517f405fc · outbound

This paper cites Opentslm: Time-series language models for reasoning over multivariate medical text-and time-series data.arXiv preprint arXiv:2510.02410, 2025.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Opentslm: Time-series language models for reasoning over multivariate medical text-and time-series data.arXiv preprint arXiv:2510.02410, 2025

Reference 7

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Observation 2bffc156-962e-47b1-819a-d7229924fcd3 · outbound

This paper cites Components of a new research resource for complex physiologic signals.Phys- ioBank, PhysioToolkit, and Physionet, 2000.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Components of a new research resource for complex physiologic signals.Phys- ioBank, PhysioToolkit, and Physionet, 2000

Reference 8

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Observation b11c73a4-1f6b-46d4-80ae-3a70a883f6d6 · outbound

This paper cites Units: A unified multi-task time series model.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Units: A unified multi-task time series model

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Observation c0974c4d-20b6-43cd-a83a-302dbd03bbdb · outbound

This paper cites John Wiley & Sons, 2015.

Frequency-Guided Deformable Networks for Continuous Phase Alignment John Wiley & Sons, 2015

Reference 10

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Observation 9baa03f0-0565-48e8-bb31-43e861236cb6 · outbound

This paper cites Forecasting seasonals and trends by exponentially weighted moving aver- ages.International journal of forecasting, 20(1):5–10, 2004.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Forecasting seasonals and trends by exponentially weighted moving aver- ages.International journal of forecasting, 20(1):5–10, 2004

Reference 11

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This paper cites Dlinear makes efficient long-term predictions.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Dlinear makes efficient long-term predictions

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Observation 32a53f5d-4e69-42d8-9a13-0fe812529568 · outbound

This paper cites GPT-4 Technical Report.

Frequency-Guided Deformable Networks for Continuous Phase Alignment GPT-4 Technical Report

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Observation 4f7a6f7a-80f5-4bff-8140-3893a14e4c60 · outbound

This paper cites The Llama 3 Herd of Models.

Frequency-Guided Deformable Networks for Continuous Phase Alignment The Llama 3 Herd of Models

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Observation 7ee4b289-fe5e-417d-a2f8-4f2e661ab18f · outbound

This paper cites Robust speech recognition via large-scale weak supervision.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Robust speech recognition via large-scale weak supervision

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This paper cites SeamlessM4T: Massively Multilingual & Multimodal Machine Translation.

Frequency-Guided Deformable Networks for Continuous Phase Alignment SeamlessM4T: Massively Multilingual & Multimodal Machine Translation

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This paper cites Scalable diffusion models with transformers.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Scalable diffusion models with transformers

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This paper cites Berg, Wan-Yen Lo, Piotr Dollar, and Ross Girshick.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Berg, Wan-Yen Lo, Piotr Dollar, and Ross Girshick

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Observation 170ead1d-74b4-4239-88de-9d3460aeb872 · outbound

This paper cites Informer: Beyond efficient transformer for long sequence time-series forecasting.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Informer: Beyond efficient transformer for long sequence time-series forecasting

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Observation 7a05af6a-8a07-4229-956c-a2ed9f0cb835 · outbound

This paper cites Autoformer: Decomposi- tion transformers with auto-correlation for long-term series forecasting.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Autoformer: Decomposi- tion transformers with auto-correlation for long-term series forecasting

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Observation 25200118-4cf2-4557-a8c6-ee12334813d1 · outbound

This paper cites A time series is worth 64 words: Long-term forecasting with transformers.

Frequency-Guided Deformable Networks for Continuous Phase Alignment A time series is worth 64 words: Long-term forecasting with transformers

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Observation f90ee967-245b-43ca-aa57-0239fa09bade · outbound

This paper cites TimeGPT-1.

Frequency-Guided Deformable Networks for Continuous Phase Alignment TimeGPT-1

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Observation 9669664e-7a6e-4db6-8898-61b4ec9a93c4 · outbound

This paper cites Maddix, Hao Wang, Michael W.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Maddix, Hao Wang, Michael W

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This paper cites Unified training of universal time series forecasting transformers.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Unified training of universal time series forecasting transformers

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Observation 11046379-d485-4c75-aa51-c51994e07356 · outbound

This paper cites Scinet: Time series modeling and forecasting with sample convolution and interaction.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Scinet: Time series modeling and forecasting with sample convolution and interaction

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Observation d12b3cdd-e432-4f97-88b7-331064713de3 · outbound

This paper cites MICN: Multi-scale local and global context modeling for long-term series forecasting.

Frequency-Guided Deformable Networks for Continuous Phase Alignment MICN: Multi-scale local and global context modeling for long-term series forecasting

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Frequency-Guided Deformable Networks for Continuous Phase Alignment ModernTCN: A modern pure convolution structure for general time series analysis

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Observation e6ea654d-30ad-4f8f-a891-f35877edfd6e · outbound

This paper cites Are transformers effective for time series forecasting? volume 37, pages 11121–11128, Jun.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Are transformers effective for time series forecasting? volume 37, pages 11121–11128, Jun

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This paper cites Why do transformers fail to forecast time series in-context?arXiv preprint arXiv:2510.09776, 2025.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Why do transformers fail to forecast time series in-context?arXiv preprint arXiv:2510.09776, 2025

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This paper cites Transformers in Time Series: A Survey.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Transformers in Time Series: A Survey

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Frequency-Guided Deformable Networks for Continuous Phase Alignment Unresolved cited work

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Frequency-Guided Deformable Networks for Continuous Phase Alignment UniConvNet: Expanding Effective Receptive Field while Maintaining Asymptotically Gaussian Distribution for ConvNets of Any Scale

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Frequency-Guided Deformable Networks for Continuous Phase Alignment M4 dataset.https://github.com/M4Competition/M4-methods/ tree/master/Dataset, 2018

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Frequency-Guided Deformable Networks for Continuous Phase Alignment Semantic-Enhanced Time-Series Forecasting via Large Language Models

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Frequency-Guided Deformable Networks for Continuous Phase Alignment Timemixer++: A general time series pattern machine for universal predictive analysis

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Frequency-Guided Deformable Networks for Continuous Phase Alignment Context-alignment: Activating and enhancing llm capabilities in time series.arXiv preprint arXiv:2501.03747, 2025

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Frequency-Guided Deformable Networks for Continuous Phase Alignment Time- VLM: Exploring multimodal vision-language models for augmented time series forecasting

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Frequency-Guided Deformable Networks for Continuous Phase Alignment Autotimes: Autoregressive time series forecasters via large language models.Advances in Neural Infor- mation Processing Systems, 37:122154–122184, 2024

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Frequency-Guided Deformable Networks for Continuous Phase Alignment S2ip-llm: Semantic space informed prompt learning with llm for time series forecast- ing

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This paper cites Zhang, Xiaoming Shi, Pin-Yu Chen, Yuxuan Liang, Yuan-Fang Li, Shirui Pan, and Qingsong Wen.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Zhang, Xiaoming Shi, Pin-Yu Chen, Yuxuan Liang, Yuan-Fang Li, Shirui Pan, and Qingsong Wen

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Frequency-Guided Deformable Networks for Continuous Phase Alignment One fits all: Power general time series analysis by pretrained lm.Advances in Neural Information Processing Systems 36, 2023

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Frequency-Guided Deformable Networks for Continuous Phase Alignment itransformer: Inverted transformers are effective for time series forecasting

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Frequency-Guided Deformable Networks for Continuous Phase Alignment Robust anomaly detection for multivariate time series through stochastic recurrent neural network

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Frequency-Guided Deformable Networks for Continuous Phase Alignment Swat: A water treatment testbed for research and training on ics security

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Frequency-Guided Deformable Networks for Continuous Phase Alignment Practical approach to asyn- chronous multivariate time series anomaly detection and localization

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Frequency-Guided Deformable Networks for Continuous Phase Alignment Anomaly transformer: Time series anomaly detection with association discrepancy

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Frequency-Guided Deformable Networks for Continuous Phase Alignment KAN-AD: Time series anomaly detection with kolmogorov–arnold networks

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Frequency-Guided Deformable Networks for Continuous Phase Alignment Non-stationary transform- ers: Exploring the stationarity in time series forecasting.Advances in neural information processing systems, 35:9881–9893, 2022

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Frequency-Guided Deformable Networks for Continuous Phase Alignment Sand: Streaming subsequence anomaly detection.Proc

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Frequency-Guided Deformable Networks for Continuous Phase Alignment Jennings

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Frequency-Guided Deformable Networks for Continuous Phase Alignment Lof: identify- ing density-based local outliers

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Frequency-Guided Deformable Networks for Continuous Phase Alignment FITS: Modeling time series with$10k$parameters

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Frequency-Guided Deformable Networks for Continuous Phase Alignment Revisiting vae for unsupervised time series anomaly detection: A frequency perspective

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Frequency-Guided Deformable Networks for Continuous Phase Alignment Shroff, and Puneet Agarwal

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Frequency-Guided Deformable Networks for Continuous Phase Alignment Hou, and Max Tegmark

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Frequency-Guided Deformable Networks for Continuous Phase Alignment Current time series anomaly detection benchmarks are flawed and are creating the illusion of progress.IEEE transactions on knowledge and data engineering, 35(3):2421–2429, 2021

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Frequency-Guided Deformable Networks for Continuous Phase Alignment The UEA multivariate time series classification archive, 2018

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Observation 2aafead3-b305-4d6e-9760-12446f82f596 · outbound

This paper cites A transformer-based framework for multivariate time series representation learn- ing.

Frequency-Guided Deformable Networks for Continuous Phase Alignment A transformer-based framework for multivariate time series representation learn- ing

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Observation ab150f36-8bb9-4c0d-9f20-1d439f10d7c2 · outbound

This paper cites Mambasl: Exploring single-layer mamba for time series classification.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Mambasl: Exploring single-layer mamba for time series classification

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This paper cites Tscmamba: Mamba meets multi-view learning for time series classification.Information Fusion, 120:103079, 2025.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Tscmamba: Mamba meets multi-view learning for time series classification.Information Fusion, 120:103079, 2025

Reference 61

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Observation e80e3cda-8400-47cd-ae81-396fa5e87113 · outbound

This paper cites Shedding light on time series classification using interpretability gated networks.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Shedding light on time series classification using interpretability gated networks

Reference 62

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Observation 37c6f933-bfd1-4a12-ad32-c37a9bd204d1 · outbound

This paper cites Tslanet: Rethinking transformers for time series representation learning.

Frequency-Guided Deformable Networks for Continuous Phase Alignment Tslanet: Rethinking transformers for time series representation learning

Reference 63

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This paper cites FEDformer: Frequency enhanced decomposed transformer for long-term series forecasting.

Frequency-Guided Deformable Networks for Continuous Phase Alignment FEDformer: Frequency enhanced decomposed transformer for long-term series forecasting

Reference 64

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