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Inference on the Angular Distribution of Extremes

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On the use of Cramér-Rao Lower Bound for least-variance circuit parameters identification of Li-ion cells

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Electrochemical Impedance Spectroscopy (EIS) and Equivalent Circuit Models (ECMs) are widely used to characterize the impedance and estimate parameters of electrochemical systems such as batteries. We use a generic ECM with ten parameters grouped to model ...

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Under resource constraints, LLMs are usually fine- tuned with additional knowledge using Parameter Efficient Fine-Tuning (PEFT), using Low-Rank Adaptation (LoRA) modules. In fact, LoRA injects a new set of small trainable matrices to adapt an LLM to a new ...

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Beyond fine-tuning: LoRA modules boost near-OOD detection and LLM security

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Under resource constraints, LLMs are usually fine-tuned with additional knowledge using Parameter Efficient Fine-Tuning (PEFT), using Low-Rank Adaptation (LoRA) modules. In fact, LoRA injects a new set of small trainable matrices to adapt an LLM to a new t ...

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On the use of Cramér-Rao Lower Bound for least-variance circuit parameters identification of Li-ion cells

Mario Paolone, Vladimir Sovljanski

2024

White adipose tissue distribution and amount are associated with increased white matter connectivity

Jean-Philippe Thiran, Gabriel Girard, Elda Fischi Gomez, Philipp Johannes Koch, Liana Okudzhava

Wiley2024

A Method of Moments Estimator for Interacting Particle Systems and their Mean Field Limit

Andrea Zanoni, Grigorios A. Pavliotis

Siam Publications2024

Instabilities in Elastic and Magneto-Elastic Beams and Shells: from Shell Buckling to the Design of a Programmable Braille Reader

Arefeh Abbasi

EPFL2024

Valence can control the nonexponential viscoelastic relaxation of multivalent reversible gels

Hugo Camille Valentin Le Roy

Amer Assoc Advancement Science2024

Graph generative deep learning models with an application to circuit topologies

Igor Krawczuk

EPFL2024

The phase-space distribution of the M 81 satellite system

Oliver Müller, Nick Heesters

Edp Sciences S A2024

Randomized low-rank approximation and its applications

Ulf David Persson

EPFL2024

Beyond fine-tuning: LoRA modules boost near-OOD detection and LLM security

Pierre Vandergheynst, Milos Vasic, Francesco Craighero, Renata Khasanova

2024

Beyond fine-tuning: LoRA modules boost near-OOD detection and LLM security

Pierre Vandergheynst, Milos Vasic, Francesco Craighero, Renata Khasanova

Under resource constraints, LLMs are usually fine-tuned with additional knowledge using Parameter Efficient Fine-Tuning (PEFT), using Low-Rank Adaptation (LoRA) modules. In fact, LoRA injects a new set of small trainable matrices to adapt an LLM to a new t ...

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