6 citations · 9 across the 5 of their papers we have counts for
5 papers
Neural Bloom: A Deep Learning Approach to Real-Time Lighting
Rafal Karp, Dawid Gruszka, Tomasz Trzcinski
We propose a novel method to generate bloom lighting effect in real time using neural networks. Our solution generate brightness mask from given 3D scene view up to 30% faster than…
ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts
Patryk Będkowski, Jan Dubiński, Filip Szatkowski +3
Simulating detector responses is a crucial part of understanding the inner workings of particle collisions in the Large Hadron Collider at CERN. Such simulations are currently perf…
Addressing The Devastating Effects Of Single-Task Data Poisoning In Exemplar-Free Continual Learning
Stanisław Pawlak, Bartłomiej Twardowski, Tomasz Trzciński +1
Our research addresses the overlooked security concerns related to data poisoning in continual learning (CL). Data poisoning - the intentional manipulation of training data to affe…
Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
Filip Szatkowski, Mateusz Pyla, Marcin Przewięźlikowski +3
In this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KD-based me…
A Deep Learning Approach for Automatic Detection of Qualitative Features of Lecturing
Anna Wroblewska, Jozef Jasek, Bogdan Jastrzebski +6
Artificial Intelligence in higher education opens new possibilities for improving the lecturing process, such as enriching didactic materials, helping in assessing students' works…