25 February 2022
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On multimodal speech-text pre-trained models

Multimodal pre-training has the potential of being a game changer in spoken language processing. In this blog, we review 3 recent papers on the topic published by Meta, Microsoft (and academic partners) and Google

2022
2 December 2021
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Deep regression on manifolds: a 3D rotation case study

Theoretical and experimental findings to improve regression applications: a 3D rotation case study. Code.

2021
29 November 2021
PoseBERT

PoseBERT

A novel, plug and play model for human 3D shape estimation of the body or hands, in videos which is trained by mimicking the BERT algorithm from the natural language processing community.
2021
4 November 2021
Towards high quality multilingual NMT in production

Towards high quality multilingual NMT in production

How to improve the inference speed of large Multilingual NTM models and do fast and parameter-efficient domain and language adaptation with them. Work published at EMNLP and WMT 2021.
2021
29 September 2021
Magnetic Sensor Based Localization

Magnetic sensor-based localization and deep learning

A novel approach to indoor localization that uses magnetic field data from smartphone sensors and deep learning
2021
30 August 2021
Learning Robot Manipulation Blog

Learning robot manipulation – modelling the reachable space of a robot and its inverse mapping

A new approach to learning few-shot imitation agents whereby you simply feed demonstrations of a new test task to the learned policy called DCRL. This new approach has several advantages.
2021
3 August 2021
EBM podcast 2021

Energy Based Models – Podcast

Podcast & edited transcript on Energy Based Models (EBMs). Guests, Hady Elsahar and Marc Dymetman work on EBMs in the field of natural language and co-organised the ICLR 2021 workshop on EBMs.
2021
15 July 2021
DCRL A new family of approaches to few-shot imitation

A new family of approaches to few-shot imitation

A new approach to learning few-shot imitation agents whereby you simply feed demonstrations of a new test task to the learned policy called DCRL. This new approach has several advantages.
2021
8 July 2021
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SPLADE – a sparse bi-encoder BERT-based model achieves effective and efficient first-stage ranking

A new sparse bi-encoder BERT-based model for effective and efficient first-stage ranking. The first to rival dense models.  
2021
21 June 2021
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Continual learning of visual representations without catastrophic forgetting

Using domain randomization and meta-learning, computer vision models forget less when exposed to training samples from new domains. Remembering is a crucial element in the deployment of self-driving cars and robots which interact in dynamic environments.
2021
19 May 2021
Localization Datasets in Crowded Indoor Spaces

Releasing first of a kind large-scale localization datasets in crowded indoor spaces

NAVER LABS releases world's biggest visual localization dataset of indoor spaces with over 130K images. Dataset built with NAVER LABS mapping robots  M1X & COMET and available in unified data format kapture.
2021
14 May 2021
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Risk-sensitive robot navigation

Using a novel algorithm we explore how effectively a single policy, learned by reinforcement learning, can modulate robot behaviour from risk-averse to risk-neutral, so that robots can safely navigate everyday environments like homes and shops.
2021

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