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Lisbon Unit for Learning and Intelligent Systems

We are pleased to announce the creation of the Lisbon Unit for Learning and Intelligent Systems (LUMLIS), a unit of the European Laboratory for Learning and Intelligent Systems (ELLIS), hosted at the Instituto Superior Técnico (IST) of the University of Lisbon (UL).

The LUMLIS Machine Learning Reading Group @ INESC-ID

This Machine Learning Reading Group meets regularly to discuss research topics on different sub-fields of Machine Learning.
INESC-ID

Reading Group Schedule

Summer Term 2020 Tuesdays at 1:00 PM
Date Presenter Topic
Feb 4 Alexandre Borges Deep Residual Learning - [paper]
Feb 11 João Monteiro Densely Connected Convolutional Networks - [paper]
Mar 3 Tomás Oliveira EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks - [paper]
Apr 7 Miguel Freire Playing Atari with Deep Reinforcement Learning - [paper]
Apr 21 Arlindo Oliveira ImageNet Classification with Deep Convolutional Meural Networks - [paper]
May 5 Luís Borges Passage Re-ranking with BERT - [paper]
May 19 Rita Ramos Show, Attend and Tell: Neural Image Caption Generation with Visual Attention - [paper]
Jun 2 Arlindo Oliveira Generative Adversarial Nets - [paper]
Jun 16 Miguel Monteiro Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty - [paper]
Jul 7 Dinis Rodrigues Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks - [paper]


Winter Term 2020 - 2021 Tuesdays at 1:00 PM
Date Presenter Topic
Sep 8 Inês Filipe Very Deep Convolutional Networks for Large-Scale Image Recognition - [paper]
Sep 22 André Godinho Recipes for building an open-domain chatbot - [paper]
Sep 29 André Cavalheiro Recurrent Neural Networks - [book chapter]
Oct 6 Rita Ramos GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks - [paper]
Oct 13 Dinis Rodrigues Automated Stenosis Detection and Classification in X-ray Angiography Using Deep Neural Network - [paper]
Oct 20 João Moura Language Models are Few-Shot Learners - [paper]
Oct 27 João Monteiro Self-training with Noisy Student improves ImageNet classification - [paper]
Nov 3 João Rico Semi-Supervised Classification with Graph Convolutional Networks - [paper]
Nov 10 Pedro Stralen Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey - [paper]
Nov 17 João Cardoso A Simple Framework for Contrastive Learning of Visual Representations - [paper]
Nov 24 Rafael Pedro Rotate to Attend: Convolutional Triplet Attention Module - [paper]
Dec 15 Tiago Mesquita Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer - [paper]
Dec 22 Mário Cardoso STConvS2S: Spatiotemporal Convolutional Sequence to Sequence Network for Weather Forecasting - [paper]
Jan 5 Susana Vinga Structured sparsity regularization for analyzing high-dimensional omics data - [paper]
Jan 12 Manuel Coimbra Modeling Relational Data with Graph Convolutional Networks - [paper]
Jan 19 Mário Figueiredo The free-energy principle a unified brain theory - [paper]
Jan 26 Tiago Oliveira Informed Machine Learning – A Taxonomy and Survey of Integrating Knowledge into Learning Systems - [paper]
Feb 2 Daniel Oliveira Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering - [paper]
Feb 9 João Cardoso COVID-19 Deterioration Prediction via Self-Supervised Representation Learning and Multi-Image Prediction - [paper]
Feb 16 Mário Cardoso RepVGG: Making VGG-style ConvNets Great Again - [paper]
Feb 23 João Barata LambdaNetworks: Modeling long-range Interactions without Attention - [paper]


Summer Term 2021 Tuesdays at 1:00 PM
Date Presenter Topic
Mar 2 Rita Ramos CPTR: Full Transformer Network for Image Captioning - [paper]
Mar 16 João Lourenço Silva SA-UNet: Spatial Attention U-Net for Retinal Vessel Segmentation - [paper]
Mar 30 Beatriz Vieira Generative Pretraining from Pixels - [paper]
Apr 13 Arlindo Oliveira The Consciousness Prior - [paper]
Apr 27 Alexandre Borges Combining Off and On-Policy Training in Model-Based Reinforcement Learning - [paper]
May 11 Nuno Infante CheXpert++: Approximating the CheXpert labeler for Speed, Differentiability, and Probabilistic Output - [paper]
May 25 Rita Ramos Unifying Vision-and-Language Tasks via Text Generation - [paper]
June 22 João Lourenço Silva Encoder-Decoder Architectures for Clinically Relevant Coronary Artery Segmentation - [paper]
June 29 Arlindo Oliveira Modeling the geospatial evolution of COVID-19 using spatio-temporal convolutional sequence-to-sequence neural networks - [paper]


Winter Term 2021 - 2022 Tuesdays at 1:00 PM
Date Presenter Topic
Sep 21 Miguel Freire CutPaste: Self-Supervised Learning for Anomaly Detection and Localization - [paper]
Sep 28 Gonçalo Raposo Efficient Nearest Neighbor Language Models - [paper]
Oct 12 Rafael Pedro ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases - [paper]
Oct 19 Rita Ramos Towards General Purpose Vision Systems - [paper]
Nov 2 João Lourenço Silva Emerging Properties in Self-Supervised Vision Transformers - [paper]
Nov 9 Isabel Coutinho "Why Should I Trust You?": Explaining the Predictions of Any Classifier - [paper]
Nov 16 João Barata Deep Learning for Remote Sensing Image Captioning (M.Sc. thesis)
Miguel Freire Evaluating generalization in Deep Reinforcement Learning with Procedurally Generated Environments (M.Sc. thesis)
Nov 23 João Silva Deep Convolutional Encoder-Decoder Architectures for Clinically Relevant Coronary Artery Segmentation (M.Sc. thesis)
Rafael Pedro Improving the Performance of Computer Vision Models with Attention Mechanisms (M.Sc. thesis)
Nov 30 Xavier Araújo A Modular Architecture for Model-Based Deep Reinforcement Learning (M.Sc. thesis)
Helena Oliveira Deep Learning-based Video Coding: Benchmarking and One Step Forward (M.Sc. thesis)
Dec 7 Pedro Mendes HyperJump: Accelerating HyperBand via Risk Modelling - [paper]
Dec 14 Luís Borges Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval - [paper]
Jan 11 José Martinho nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation - [paper]
Jan 18 Gonçalo Oliveira Siamese Neural Networks for One-shot Image Recognition - [paper]
Jan 25 Gonçalo Raposo Improving language models by retrieving from trillions of tokens - [paper]
Feb 1 João Daniel Silva Learning Transferable Visual Models From Natural Language Supervision - [paper]
Feb 8 Gonçalo Oliveira Attention-based Deep Multiple Instance Learning - [paper]
Feb 15 Joseph J. Paton Manipulation of striatal population dynamics using temperature warps judgment of time - [paper]


Summer Term 2022 Tuesdays at 1:00 PM
Date Presenter Topic
Mar 15 João Silva A ConvNet for the 2020s - [paper]
Mar 29 Bálint Magyar Sanity Checks for Saliency Maps - [paper]
Apr 12 Diogo Moura FLAVA: A Foundational Language And Vision Alignment Model - [paper]
May 10 Batriz Vieira Using a Siamese Network to Accurately Detect Ischemic Stroke in Computed Tomography Scans - [paper]
May 24 Tiago Marques Building integrative systems-level models for neuroscience and artificial intelligence - [paper]
Jun 7 João Sacramento A contrastive rule for meta-learning - [paper]
Jun 21 Anderson Rocha Reasoning for Complex Data through Ensemble-based Self-Supervised Learning - [paper]


Winter Term 2022 - 2023 Tuesdays at 1:00 PM
Date Presenter Topic
Sep 13 Tiago Oliveira Revisiting ResNets: Improved Training and Scaling Strategies - [paper]
Sep 20 João Daniel Silva Compositional Attention: Disentangling Search and Retrieval - [paper]
Sep 27 Manuel Blum and Lenore Blum The Conscious Turing Machine: A Framework for a Conscious AI - [paper]
Oct 4 Luís Borges Text-to-Text Multi-view Learning for Passage Re-ranking - [paper]
Oct 11 Miguel Freire High-Resolution Image Synthesis with Latent Diffusion Models - [paper]
Oct 18 Tiago Oliveira ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness - [paper]
Oct 25 António Pereira Swin Transformer V2: Scaling Up Capacity and Resolution - [paper]
Nov 8 André Duarte Siamese Transformer Networks for Improving Address Matching (M.Sc. thesis) - [paper]
Nichal Narotamo Conversational Question Re-Writing (M.Sc. thesis) - [paper]
Nov 15 Gonçalo Oliveira Towards Improving Ischemic Stroke Functional Outcome Prediction with Computed Tomography Brain Scans Using Deep Learning (M.Sc. thesis) - [paper]
Manuel Goulão Pretraining the Vision Transformer using self-supervised methods for vision-based deep reinforcement learning (M.Sc. thesis) - [paper]
Nov 22 José Pereira Old photo and image restoration using deep learning techniques (M.Sc. thesis) - [paper]
António Pereira Comparison of semantic context and inductive biases on self-attention based models (M.Sc. thesis) - [paper]
Nov 29 Gonçalo Mendes Estimating Emotional Valence and Arousal with Transformer-Based Language Models (M.Sc. thesis) - [paper]
João Saraiva Deep Residual Learning for Epileptic Seizure Prediction and Tools to Expedite Biosignal Research (M.Sc. thesis) - [paper]
Dec 6 To be announced To be announced - [paper]