TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection | Paper Citation Record

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TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection Unresolved cited work

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This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

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TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection Unresolved cited work

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TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection Unresolved cited work

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TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection Unresolved cited work

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This paper cites Time-Series Anomaly Detection with Implicit Neural Representation.

TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection Time-Series Anomaly Detection with Implicit Neural Representation

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This paper cites Katser and Vyacheslav O.

TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection Katser and Vyacheslav O

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This paper cites Adam: A Method for Stochastic Optimization.

TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection Adam: A Method for Stochastic Optimization

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TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection Unresolved cited work

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TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection Unresolved cited work

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TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection Unresolved cited work

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TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection ETSformer: Exponential Smoothing Transformers for Time-series Forecasting

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Reference 57

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TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection Unresolved cited work

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This paper cites Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy.

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Reference 60

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Reference 66

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Reference 70

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Reference 71

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Reference 72

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Observation f337cce2-a16d-467c-ba07-1ba850759cdb · outbound

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Reference 73

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Observation 378f9d78-cc51-4d32-991a-2485866e47cf · outbound

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Reference 76

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TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection In International Conference on Machine Learning

Reference 78

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Reference 1990

Resolution: unresolved; raw_fallback, observed 2026-08-12T18:20:55.998729Z

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Observation 869e4aab-6c70-4589-8608-8cb0220d6831 · outbound

This paper cites Advances in Neural Information Processing Systems 33 (2020), 7537–7547.

TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection Advances in Neural Information Processing Systems 33 (2020), 7537–7547

Reference 2020

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Observation a708a647-a244-4ddd-a539-468fa458a4ce · outbound

This paper cites PeerJ Computer Science 7 (2021), e757.

TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection PeerJ Computer Science 7 (2021), e757

Reference 2021

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TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection In European Con- ference on Computer Vision

Reference 2022

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Observation 841cc6e5-5557-4e8e-8fe2-ea18f62f5018 · outbound

This paper cites IEEE Transactions on Neural Networks and Learning Systems (2023), 1–12.

TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection IEEE Transactions on Neural Networks and Learning Systems (2023), 1–12

Reference 2023

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Unavailable: canonical work link unavailable.

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Reference resolution

Outbound references

Pith citing papers