Minimize experimentation overhead through dataset selection, ensemble feature attention, and feature selection with reduced subset sizes

Benchmarking Neural Decoders: Benchmarking of Hardware-efficient Real-time Neural Decoding in Brain-computer Interfaces

Backdoor attacks in federated learning with regression

Scale Learning in Scale-Equivariant Convolutional networks

Making it Clear: Using Vision Transformers in Multi-View Stereo on Specular and Transparent Materials

MAPL: Model Agnostic Peer-to-Peer Learning

Combining denoising and object detection: An analysis to provide insights in combining denoising with object detection

Neural Radiance Field (NeRF) as a Rendering Primitive: StreamNeRF - Adapting a NeRF Model for Progressive Decoding

Depth Light Field Training (DeLFT): NeRF as a rendering primitive

Using K-Means clustering to export a NeRF for faster rendering in CG applications while preserving view-dependent appearance

Non-Photorealistic Novel View Synthesis Using Radiance Fields

EasyCompress: Automated Compression for Deep Learning Models

Optimizing Event-Based Vision by Realizing Super-Resolution in Event-Space: an Experimental Approach

Semi auto-taggers for music: Combining audio content and human annotations for tag prediction

Outcome prediction for endovascular therapy: Multimodal deep learning for acute ischemic events in the arteria cerebri media

Detecting Medical Equipment in the Catheterization Laboratory using Computer Vision

The effect of recurrence on adversarial robustness

Self-Supervised Few Shot Learning: Prototypical Contrastive Learning with Graphs

TRIDENT: Transductive Variational Inference of Decoupled Latent Variables for Few Shot Classification

Prediction of blood volume pulse waveform features using remote PPG