2 citations · 2 across the 6 of their papers we have counts for
6 papers
Prof-K: Probabilistic One-Pass Filtering for Efficient Top-k Selection
Tadeusz Dziarmaga, Witold Sikora, Łukasz Struski +2
Top-k selection is a fundamental computational primitive with applications spanning databases, information retrieval, signal processing, and modern machine learning workloads, incl…
CLIPGaussian: Universal and Multimodal Style Transfer Based on Gaussian Splatting
Kornel Howil, Joanna Waczyńska, Piotr Borycki +3
Gaussian Splatting (GS) has recently emerged as an efficient representation for rendering 3D scenes from 2D images and has been extended to images, videos, and dynamic 4D content.…
PALATE: Peculiar Application of the Law of Total Expectation to Enhance the Evaluation of Deep Generative Models
Tadeusz Dziarmaga, Marcin Kądziołka, Artur Kasymov +4
Deep generative models (DGMs) have caused a paradigm shift in the field of machine learning, yielding noteworthy advancements in domains such as image synthesis, natural language p…
Tight Bounds for Jensen's Gap with Applications to Variational Inference
Marcin Mazur, Tadeusz Dziarmaga, Piotr Kościelniak +1
Since its original formulation, Jensen's inequality has played a fundamental role across mathematics, statistics, and machine learning, with its probabilistic version highlighting…
RaySplats: Ray Tracing based Gaussian Splatting
Krzysztof Byrski, Marcin Mazur, Jacek Tabor +4
3D Gaussian Splatting (3DGS) is a process that enables the direct creation of 3D objects from 2D images. This representation offers numerous advantages, including rapid training an…
Accelerating Goal-Conditioned RL Algorithms and Research
Michał Bortkiewicz, Władysław Pałucki, Vivek Myers +4
Self-supervision has the potential to transform reinforcement learning (RL), paralleling the breakthroughs it has enabled in other areas of machine learning. While self-supervised…