Publications
The Nabla team is at the forefront of machine learning & healthcare research.
This helps us deliver the most advanced medical scribe technology, and contribute back to 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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