8 citations · 12 across the 6 of their papers we have counts for
7 papers
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…
Enhancing Time Series Forecasting with Fuzzy Attention-Integrated Transformers
Sanjay Chakraborty, Fredrik Heintz
This paper introduces FANTF (Fuzzy Attention Network-Based Transformers), a novel approach that integrates fuzzy logic with existing transformer architectures to advance time serie…
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…
Generative AI in Modern Education Society
Sanjay Chakraborty
Transitioning from Education 1.0 to Education 5.0, the integration of generative artificial intelligence (GenAI) revolutionizes the learning environment by fostering enhanced human…