Université de Montréal

Gradient-based learning applied to document recognition

Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradient based learning technique. Given an appropriate networ...

Issues and challenges facing rechargeable lithium batteries

Representation Learning: A Review and New Perspectives

The success of machine learning algorithms generally depends on data representation, and we hypothesize that this is because different representations can entangle and hide more...

Generative adversarial networks

Generative adversarial networks are a kind of artificial intelligence algorithm designed to solve the generative modeling problem. The goal of a generative model is to study a c...

Observation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC

European Position Paper on Rhinosinusitis and Nasal Polyps 2020

The European Position Paper on Rhinosinusitis and Nasal Polyps 2020 is the update of similar evidence based position papers published in 2005 and 2007 and 2012. The core objecti...

Tisagenlecleucel in Children and Young Adults with B-Cell Lymphoblastic Leukemia

In this global study of CAR T-cell therapy, a single infusion of tisagenlecleucel provided durable remission with long-term persistence in pediatric and young adult patients wit...

Generative Adversarial Networks: An Overview

Generative adversarial networks (GANs) provide a way to learn deep representations without extensively annotated training data. They achieve this by deriving backpropagation sig...

Tisagenlecleucel in Adult Relapsed or Refractory Diffuse Large B-Cell Lymphoma

In this international study of CAR T-cell therapy in relapsed or refractory diffuse large B-cell lymphoma in adults, high rates of durable responses were produced with the use o...

The 5th edition of the World Health Organization Classification of Haematolymphoid Tumours: Myeloid and Histiocytic/Dendritic Neoplasms