Tomasz Trzciński

research

∙ 09/18/2023

AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation

Test-time adaptation is a promising research direction that allows the s...

0 Damian Sójka, et al. ∙

research

∙ 09/18/2023

Looking through the past: better knowledge retention for generative replay in continual learning

In this work, we improve the generative replay in a continual learning s...

0 Valeriya Khan, et al. ∙

research

∙ 08/18/2023

Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning

In this work, we investigate exemplar-free class incremental learning (C...

0 Filip Szatkowski, et al. ∙

research

∙ 06/23/2023

Machine Learning methods for simulating particle response in the Zero Degree Calorimeter at the ALICE experiment, CERN

Currently, over half of the computing power at CERN GRID is used to run ...

0 Jan Dubiński, et al. ∙

research

∙ 06/22/2023

Towards More Realistic Membership Inference Attacks on Large Diffusion Models

Generative diffusion models, including Stable Diffusion and Midjourney, ...

0 Jan Dubiński, et al. ∙

research

∙ 05/31/2023

The Tunnel Effect: Building Data Representations in Deep Neural Networks

Deep neural networks are widely known for their remarkable effectiveness...

0 Wojciech Masarczyk, et al. ∙

research

∙ 05/12/2023

BlendFields: Few-Shot Example-Driven Facial Modeling

Generating faithful visualizations of human faces requires capturing bot...

0 Kacper Kania, et al. ∙

research

∙ 03/27/2023

Exploring Continual Learning of Diffusion Models

Diffusion models have achieved remarkable success in generating high-qua...

0 Michał Zając, et al. ∙

research

∙ 02/09/2023

Hypernetworks build Implicit Neural Representations of Sounds

Implicit Neural Representations (INRs) are nowadays used to represent mu...

0 Filip Szatkowski, et al. ∙

research

∙ 02/07/2023

Can gamification reduce the burden of self-reporting in mHealth applications? Feasibility study using machine learning from smartwatch data to estimate cognitive load

The effectiveness of digital treatments can be measured by requiring pat...

0 Michał K. Grzeszczyk, et al. ∙

research

∙ 01/31/2023

Learning Data Representations with Joint Diffusion Models

We introduce a joint diffusion model that simultaneously learns meaningf...

0 Kamil Deja, et al. ∙

research

∙ 12/20/2022

Towards Unsupervised Visual Reasoning: Do Off-The-Shelf Features Know How to Reason?

Recent advances in visual representation learning allowed to build an ab...

0 Monika Wysoczanska, et al. ∙

research

∙ 11/11/2022

Emergency action termination for immediate reaction in hierarchical reinforcement learning

Hierarchical decomposition of control is unavoidable in large dynamical ...

0 Michał Bortkiewicz, et al. ∙

research

∙ 11/03/2022

HyperSound: Generating Implicit Neural Representations of Audio Signals with Hypernetworks

Implicit neural representations (INRs) are a rapidly growing research fi...

0 Filip Szatkowski, et al. ∙

research

∙ 07/04/2022

Progressive Latent Replay for efficient Generative Rehearsal

We introduce a new method for internal replay that modulates the frequen...

3 Stanislaw Pawlak, et al. ∙

research

∙ 07/04/2022

Selectively increasing the diversity of GAN-generated samples

Generative Adversarial Networks (GANs) are powerful models able to synth...

0 Jan Dubiński, et al. ∙

research

∙ 06/16/2022

Continual Learning with Guarantees via Weight Interval Constraints

We introduce a new training paradigm that enforces interval constraints ...

0 Maciej Wołczyk, et al. ∙

research

∙ 05/31/2022

On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models

Diffusion-based Deep Generative Models (DDGMs) offer state-of-the-art pe...

0 Kamil Deja, et al. ∙

research

∙ 05/30/2022

A Deep Learning Approach for Automatic Detection of Qualitative Features of Lecturing

Artificial Intelligence in higher education opens new possibilities for ...

0 Anna Wroblewska, et al. ∙

research

∙ 05/27/2022

Deep Learning Fetal Ultrasound Video Model Match Human Observers in Biometric Measurements

Objective. This work investigates the use of deep convolutional neural n...

0 Szymon Płotka, et al. ∙

research

∙ 05/19/2022

BabyNet: Residual Transformer Module for Birth Weight Prediction on Fetal Ultrasound Video

Predicting fetal weight at birth is an important aspect of perinatal car...

0 Szymon Płotka, et al. ∙

research

∙ 05/16/2022

Continual learning on 3D point clouds with random compressed rehearsal

Contemporary deep neural networks offer state-of-the-art results when ap...

0 Maciej Zamorski, et al. ∙

research

∙ 01/23/2022

POTHER: Patch-Voted Deep Learning-based Chest X-ray Bias Analysis for COVID-19 Detection

A critical step in the fight against COVID-19, which continues to have a...

16 Tomasz Szczepański, et al. ∙

research

∙ 01/17/2022

Logarithmic Continual Learning

We introduce a neural network architecture that logarithmically reduces ...

0 Wojciech Masarczyk, et al. ∙

research

∙ 12/03/2021

CoNeRF: Controllable Neural Radiance Fields

We extend neural 3D representations to allow for intuitive and interpret...

0 Kacper Kania, et al. ∙

research

∙ 10/26/2021

Non-Gaussian Gaussian Processes for Few-Shot Regression

Gaussian Processes (GPs) have been widely used in machine learning to mo...

11 Marcin Sendera, et al. ∙

research

∙ 10/24/2021

EgoNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale

The paper presents a deep neural network-based method for global and loc...

0 Jacek Komorowski, et al. ∙

research

∙ 10/12/2021

HyperCube: Implicit Field Representations of Voxelized 3D Models

Recently introduced implicit field representations offer an effective wa...

0 Magdalena Proszewska, et al. ∙

research

∙ 10/06/2021

Large-Scale Topological Radar Localization Using Learned Descriptors

In this work, we propose a method for large-scale topological localizati...

0 Jacek Komorowski, et al. ∙

research

∙ 10/05/2021

Efficient GPU implementation of randomized SVD and its applications

Matrix decompositions are ubiquitous in machine learning, including appl...

0 Łukasz Struski, et al. ∙

research

∙ 09/04/2021

On robustness of generative representations against catastrophic forgetting

Catastrophic forgetting of previously learned knowledge while learning n...

0 Wojciech Masarczyk, et al. ∙

research

∙ 08/03/2021

HyperColor: A HyperNetwork Approach for Synthesizing Auto-colored 3D Models for Game Scenes Population

Designing a 3D game scene is a tedious task that often requires a substa...

7 Ivan Kostiuk, et al. ∙

research

∙ 07/14/2021

FetalNet: Multi-task deep learning framework for fetal ultrasound biometric measurements

In this paper, we propose an end-to-end multi-task neural network called...

0 Szymon Płotka, et al. ∙

research

∙ 06/23/2021

Multiband VAE: Latent Space Partitioning for Knowledge Consolidation in Continual Learning

We propose a new method for unsupervised continual knowledge consolidati...

0 Kamil Deja, et al. ∙

research

∙ 06/21/2021

Visual Probing: Cognitive Framework for Explaining Self-Supervised Image Representations

Recently introduced self-supervised methods for image representation lea...

0 Witold Oleszkiewicz, et al. ∙

research

∙ 06/09/2021

Zero Time Waste: Recycling Predictions in Early Exit Neural Networks

The problem of reducing processing time of large deep learning models is...

0 Maciej Wołczyk, et al. ∙

research

∙ 04/18/2021

Convolutional Neural Networks in Orthodontics: a review

Convolutional neural networks (CNNs) are used in many areas of computer ...

3 Szymon Płotka, et al. ∙

research

∙ 04/12/2021

MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition

We introduce a discriminative multimodal descriptor based on a pair of s...

0 Jacek Komorowski, et al. ∙

research

∙ 04/01/2021

TrajeVAE – Controllable Human Motion Generation from Trajectories

The generation of plausible and controllable 3D human motion animations ...

0 Kacper Kania, et al. ∙

research

∙ 02/17/2021

I Want This Product but Different : Multimodal Retrieval with Synthetic Query Expansion

This paper addresses the problem of media retrieval using a multimodal q...

0 Ivona Tautkute, et al. ∙

research

∙ 02/11/2021

Modeling 3D Surface Manifolds with a Locally Conditioned Atlas

Recently proposed 3D object reconstruction methods represent a mesh with...

12 Przemysław Spurek, et al. ∙

research

∙ 02/11/2021

HyperPocket: Generative Point Cloud Completion

Scanning real-life scenes with modern registration devices typically giv...

4 Przemysław Spurek, et al. ∙

research

∙ 11/30/2020

RegFlow: Probabilistic Flow-based Regression for Future Prediction

Predicting future states or actions of a given system remains a fundamen...

0 Maciej Zieba, et al. ∙

research

∙ 08/16/2020

Spontaneous preterm birth prediction using convolutional neural networks

An estimated 15 million babies are born too early every year. Approximat...

11 Tomasz Włodarczyk, et al. ∙

research

∙ 06/15/2020

HyperFlow: Representing 3D Objects as Surfaces

In this work, we present HyperFlow - a novel generative model that lever...

0 Przemysław Spurek, et al. ∙

research

∙ 06/11/2020

End-to-end Sinkhorn Autoencoder with Noise Generator

In this work, we propose a novel end-to-end sinkhorn autoencoder with no...

12 Kamil Deja, et al. ∙

research

∙ 03/23/2020

Understanding the robustness of deep neural network classifiers for breast cancer screening

Deep neural networks (DNNs) show promise in breast cancer screening, but...

10 Witold Oleszkiewicz, et al. ∙

research

∙ 12/10/2019

SuperNCN: Neighbourhood consensus network for robust outdoor scenes matching

In this paper, we present a framework for computing dense keypoint corre...

0 Grzegorz Kurzejamski, et al. ∙

research

∙ 09/11/2019

Late fusion of deep learning and hand-crafted features for Achilles tendon healing monitoring

Healing process assessment of the Achilles tendon is usually a complex p...

0 Norbert Kapinski, et al. ∙

research

∙ 09/11/2019

Monitoring Achilles tendon healing progress in ultrasound imaging with convolutional neural networks

Achilles tendon rupture is a debilitating injury, which is typically tre...

0 Piotr Woznicki, et al. ∙

Tomasz Trzciński

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