Publication

Sparse Autoencoders for Speech Modeling and Recognition

About
Privacy
Disclaimer

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Sparse Autoencoders for Speech Modeling and Recognition

Graph Chatbot

Chat with Graph Search

Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Training a Filter-Based Model of the Cochlea in the Context of Pre-Trained Acoustic Models

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs

Aggregating Spatial and Photometric Context for Photometric Stereo

Topics in statistical physics of high-dimensional machine learning

Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks

InterpretCC: Intrinsic User-Centric Interpretability through Global Mixture of Experts

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks