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cs.LG2024
Filtered not Mixed: Stochastic Filtering-Based Online Gating for Mixture of Large Language Models
Raeid Saqur, Anastasis Kratsios, Florian Krach +5
We propose MoE-F - a formalized mechanism for combining pre-trained Large Language Models (LLMs) for online time-series prediction by adaptively forecasting the best weighting…
cs.LG2024
Higher-Order Transformer Derivative Estimates for Explicit Pathwise Learning Guarantees
Yannick Limmer, Anastasis Kratsios, Xuwei Yang +2
An inherent challenge in computing fully-explicit generalization bounds for transformers involves obtaining covering number estimates for the given transformer class . Crude est…
cs.LG2023
Transformers Can Solve Non-Linear and Non-Markovian Filtering Problems in Continuous Time For Conditionally Gaussian Signals
Blanka Horvath, Anastasis Kratsios, Yannick Limmer +1
The use of attention-based deep learning models in stochastic filtering, e.g. transformers and deep Kalman filters, has recently come into focus; however, the potential for these m…