Back to Research

Research Papers

TunBERT: Pretrained Contextualized Text Representation for Tunisian Dialect

Hatem Haddad | Abir Messaoudi | Chayma Fourati | Moez Ben HajHmida | Ahmed Cheikh Rouhou | Abir Korched | Amel Sellami | Faten Ghriss

Mar 2024

TunBERT: Pretrained Contextualized Text Representation for Tunisian Dialect

FULL PAPER Read More

Graph Neural Networks for End-to-End Information Extraction from Handwritten Documents

Yessine Khanfir | Marwa Dhiaf | Emna Ghodhbani | Ahmed Cheikh Rouhou | Yousri Kessentini

WACV 2024 Mar 2024

Graph Neural Networks for End-to-End Information Extraction from Handwritten Documents

FULL PAPER Read More

BioCLIP: Contrasting Sequence with Structure: Pre-training Graph Representations with Protein Language Models

Louis Robinson | Timothy Atkinson | Liviu Copoiu | Patrick Bordes | Thomas Pierrot | Thomas D. Barrett

NeurIPS workshop Dec 2023

BioCLIP, a self-supervised contrastive learning framework for generating Protein Structure Models (PSMs) based on Protein Language Models (PLMs) like ESM2

FULL PAPER GITHUB Read More

Generalisable Agents for Neural Network Optimisation

Kale-ab Tessera | Callum Rhys Tilbury | Sasha Abramowitz | Ruan de Kock | Omayma Mahjoub | Benjamin Rosman | Sara Hooker | Arnu Pretorius

NeurIPS workshop Dec 2023

Optimising deep neural networks with framework of Generalisable Agents for Neural Network Optimisation (GANNO) — a multi-agent reinforcement learning (MARL) approach that learns to improve neural network optimisation by dynamically and responsively scheduling hyperparameters during training

FULL PAPER Read More

Offline RL for generative design of protein binders

Denis Tarasov | Ulrich A. Mbou Sob | Miguel Arbesú | Nima Siboni | Sebastien Boyer | Andries Smit | Oliver Bent | Arnu Pretorius

NeurIPS workshop Dec 2023

a study on the application of offline Reinforcement Learning (RL) to address the bottleneck posed by the docking process, leveraging RL’s capability to optimize non-differentiable properties.

FULL PAPER Read More

Preferential Bayesian Optimisation for Protein Design with Fine-Tuned Protein Language Model Ensembles

Alex Hawkins-Hooker | Paul Duckworth | Oliver Bent

NeurIPS workshop Dec 2023

FULL PAPER Read More

FrameDiPT: SE(3) Diffusion Model for Protein Structure Inpainting

Cheng Zhang | Adam Leach | Tom Makkink | Miguel Arbesu | Ibtissem Kadri | Daniel Luo | Liron Mizrahi | Sabrine Krichen | Maren Lang | Andrey Tovchigrechko | Nicolas Lopez Carranza | Ugur Sahin | Karim Beguir | Michael Rooney | Yunguan Fu

NeurIPS workshop Dec 2023

FULL PAPER Read More

Are we going MAD? Benchmarking Multi-Agent Debate between Language Models for Medical Q&A

Dries Smit | Paul Duckworth | Nathan Grinsztajn | Kale-ab Tessera | Tom Barrett | Arnu Pretorius

NeurIPS workshop Dec 2023

FULL PAPER Read More

LightMHC: A Light Model for pMHC Structure Prediction with Graph Neural Networks

Antoine Delaunay | Yunguan Fu | Nikolai Gorbushin | Robert McHardy | Bachir Djermani | Liviu Copoiu | Michael Rooney | Maren Lang | Andrey Tovchigrechko | Ugur Sahin | Karim Beguir | Nicolas Lopez Carranza

NeurIPS workshop Dec 2023

FULL PAPER Read More

PASTA: Pretrained Action-State Transformer Agents

Raphael Boige | Yannis Flet-Berliac | Arthur Flajolet | Guillaume Richard | Thomas Pierrot

NeurIPS workshop Dec 2023

FULL PAPER Read More

Combinatorial Optimization with Policy Adaptation using Latent Space Search

Felix Chalumeau | Shikha Surana | Clement Bonnet | Nathan Grinsztajn | Arnu Pretorius | Alexandre Laterre | Thomas D. Barrett

NeurIPS workshop Dec 2023

FULL PAPER Read More

Nonparametric Boundary Geometry in Physics Informed Deep Learning

Scott Cameron | Arnu Pretorius | Stephen Roberts

NeurIPS Dec 2023

FULL PAPER Read More