10 citations · 28 across the 10 of their papers we have counts for
12 papers
Visual Probing: Cognitive Framework for Explaining Self-Supervised Image Representations
Witold Oleszkiewicz, Dominika Basaj, Igor Sieradzki +5
Recently introduced self-supervised methods for image representation learning provide on par or superior results to their fully supervised competitors, yet the corresponding effort…
T-EMDE: Sketching-based global similarity for cross-modal retrieval
Barbara Rychalska, Mikolaj Wieczorek, Jacek Dabrowski
The key challenge in cross-modal retrieval is to find similarities between objects represented with different modalities, such as image and text. However, each modality embeddings…
On the Unreasonable Effectiveness of Centroids in Image Retrieval
Mikolaj Wieczorek, Barbara Rychalska, Jacek Dabrowski
Image retrieval task consists of finding similar images to a query image from a set of gallery (database) images. Such systems are used in various applications e.g. person re-ident…
Modeling Multi-Destination Trips with Sketch-Based Model
Michał Daniluk, Barbara Rychalska, Konrad Gołuchowski +1
The recently proposed EMDE (Efficient Manifold Density Estimator) model achieves state of-the-art results in session-based recommendation. In this work we explore its application t…
Cleora: A Simple, Strong and Scalable Graph Embedding Scheme
Barbara Rychalska, Piotr Bąbel, Konrad Gołuchowski +2
The area of graph embeddings is currently dominated by contrastive learning methods, which demand formulation of an explicit objective function and sampling of positive and negativ…
I know why you like this movie: Interpretable Efficient Multimodal Recommender
Barbara Rychalska, Dominika Basaj, Jacek Dąbrowski +1
Recently, the Efficient Manifold Density Estimator (EMDE) model has been introduced. The model exploits Local Sensitive Hashing and Count-Min Sketch algorithms, combining them with…