2 citations · 4 across the 6 of their papers we have counts for
7 papers
A Quantum-Classical Hybrid Framework for Multivariate Time-Series Forecasting Complexity-Fidelity Trade-offs and Limitations
Sanjay Chakraborty, Fredrik Heintz
This paper presents a unified quantum-classical hybrid framework for multi-horizon time-series forecasting, introducing two model variants Quantum Reservoir Forecaster (QRC-F) and…
Learning Temporal Saliency for Time Series Forecasting with Cross-Scale Attention
Ibrahim Delibasoglu, Fredrik Heintz
Explainability in time series forecasting is essential for improving model transparency and supporting informed decision-making. In this work, we present CrossScaleNet, an innovati…
Scaling Transformers for Time Series Forecasting: Do Pretrained Large Models Outperform Small-Scale Alternatives?
Sanjay Chakraborty, Ibrahim Delibasoglu, Fredrik Heintz
Large pre-trained models have demonstrated remarkable capabilities across domains, but their effectiveness in time series forecasting remains understudied. This work empirically ex…
FANTF: Fuzzy attention network based transformers for time series analysis
Sanjay Chakraborty, Fredrik Heintz
This paper introduces Fuzzy Attention Network-Based Transformer (FANTF), an approach for time series forecasting, classification, and anomaly detection. FANTF combines fuzzy logic…
Integrating Quantum-Classical Attention in Patch Transformers for Enhanced Time Series Forecasting
Sanjay Chakraborty, Fredrik Heintz
QCAAPatchTF is a quantum attention network integrated with an advanced patch-based transformer, designed for multivariate time series forecasting, classification, and anomaly detec…
LMS-AutoTSF: Learnable Multi-Scale Decomposition and Integrated Autocorrelation for Time Series Forecasting
Ibrahim Delibasoglu, Sanjay Chakraborty, Fredrik Heintz
Time series forecasting is an important challenge with significant applications in areas such as weather prediction, stock market analysis, scientific simulations and industrial pr…
EDformer: Embedded Decomposition Transformer for Interpretable Multivariate Time Series Predictions
Sanjay Chakraborty, Ibrahim Delibasoglu, Fredrik Heintz
Time series forecasting is a crucial challenge with significant applications in areas such as weather prediction, stock market analysis, and scientific simulations. This paper intr…