Publications
L'équipe de Nabla conduit des recherches fondamentales en machine learning et en santé.
C'est ainsi que nous construisons l'assistant médical le plus avancé, tout en faisant progresser la science.
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Martin Raison
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fastMRI: An open dataset and benchmarks for accelerated MRI
Ruben Stern
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Poly-encoders: Transformer architectures and pre-training strategies for fast and accurate multi-sentence scoring
Sam Humeau
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Training millions of personalized dialogue agents
Sam Humeau
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Build it break it fix it for dialogue safety: Robustness from adversarial human attack
Sam Humeau
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Using deep learning to accelerate knee MRI at 3 T: results of an interchangeability study
Ruben Stern
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Ranked reward: Enabling self-play reinforcement learning for combinatorial optimization
Karl Hajjar
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TorchKbNufft: A high-level, hardware-agnostic non-uniform fast Fourier transform
Ruben Stern
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Real-time inference in multi-sentence tasks with deep pretrained transformers
Sam Humeau
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Multimodal attribute extraction
Sam Humeau
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Weaver: Deep co-encoding of questions and documents for machine reading
Martin Raison
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Inferring Transmission Histories of Rare Alleles in Population-Scale Genealogies
Marianne de Vriendt
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The GraphNet zoo: an all-in-one graph based deep semi-supervised framework for medical image classification
Marianne de Vriendt
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Training integrable parameterizations of deep neural networks in the infinite-width limit
Karl Hajjar
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Uncertainty-aware automated assessment of the arm impedance with upper-limb exoskeletons
Ronan Sangouard
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Aggregating similarity metrics for natural language generation
Grégoire Retourné
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Score-Based Generative Modeling through Stochastic Differential Equations, a review
Grégoire Retourné
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