Publications associées à Implicit memory

Bit-Line Computing for CNN Accelerators Co-Design in Edge AI Inference

David Atienza Alonso, Giovanni Ansaloni, Alexandre Sébastien Julien Levisse, Marco Antonio Rios, Flavio Ponzina

By supporting the access of multiple memory words at the same time, Bit-line Computing (BC) architectures allow the parallel execution of bit-wise operations in-memory. At the array periphery, arithmetic operations are then derived with little additional o ...

2023

Noninvasive deep brain stimulation to modulate human behavior by means of transcranial temporal interference electrical stimulation

Elena Beanato

All functions we use in our everyday life depend on a complex interplay between both cortical and subcortical brain areas, communicating in between each others. When a region is affected by either an accident, aging or neurodegenerative diseases, the whole ...

EPFL2023

KNNs of Semantic Encodings for Rating Prediction

Léo Jules Laugier

This paper explores a novel application of textual semantic similarity to user-preference representation for rating prediction. The approach represents a user's preferences as a graph of textual snippets from review text, where the edges are defined by sem ...

IEEE2023

The role of secondary features in serial dependence

David Pascucci

Recent work indicates that visual features are processed in a serially dependent manner: The decision about a stimulus feature in the present is influenced by the features of stimuli seen in the past, leading to serial dependence. It remains unclear, howev ...

2023

How to Achieve Large-Area Ultra-Fast Operation of MoS 2 Monolayer Flash Memories?

Aleksandra Radenovic, Andras Kis, Mukesh Kumar Tripathi, Asmund Kjellegaard Ottesen, Yanfei Zhao, Guilherme Migliato Marega, Zhenyu Wang, Hyungoo Ji

Memory devices have returned to the spotlight due to increasing interest in using in-memory computing architectures to make data-driven algorithms more energy-efficient. One of the main advantages of this architecture is the efficient performance of vector ...

2023

A dynamic attractor network model of memory formation, reinforcement and forgetting

Wulfram Gerstner, Chiara Gastaldi, Marta Boscaglia

Empirical evidence shows that memories that are frequently revisited are easy to recall, and that familiar items involve larger hippocampal representations than less familiar ones. In line with these observations, here we develop a modelling approach to pr ...

Public Library Science2023

A 16-bit Floating-Point Near-SRAM Architecture for Low-power Sparse Matrix-Vector Multiplication

David Atienza Alonso, Giovanni Ansaloni, Grégoire Axel Eggermann, Marco Antonio Rios

State-of-the-art Artificial Intelligence (AI) algorithms, such as graph neural networks and recommendation systems, require floating-point computation of very large matrix multiplications over sparse data. Their execution in resource-constrained scenarios, ...

New York2023

Perceptual Learning: Policy Insights From Basic Research to Real-World Applications

Michael Herzog

Perceptual learning is the process by which experience alters how incoming sensory information is processed by the brain to give rise to behavior-it is critical for how humans educate children, train experts, treat diseases, and promote health and well-bei ...

Sage Publications Inc2023

Bodily self-consciousness as a framework to link sensory information and self-related components of episodic memory: behavioral, neuroimaging, and clinical evidence

Nathalie Heidi Meyer

The recollection of sensory information and subjective experience related to a personal past event depends on our episodic memory (EM). At the neural level, EM retrieval is linked with the reinstatement of hippocampal activity thought to recollect the sens ...

EPFL2023

Memory-Based Model Editing at Scale

Antoine Bosselut

Even the largest neural networks make errors, and once-correct predictions can become invalid as the world changes. Model editors make local updates to the behavior of base (pre-trained) models to inject updated knowledge or correct undesirable behaviors. ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2022