🏢 University of Edinburgh

Using tropical geometry, researchers reveal that ReLU-activated message-passing GNNs learn continuous piecewise linear functions, highlighting their expressivity limits and paving the way for enhanced…

Wasserstein Gradient Boosting (WGBoost) extends gradient boosting to handle probability distributions as outputs, enabling more robust and informative predictions in various applications.

New topology-based complexity measures reliably predict deep learning model generalization, outperforming existing methods and offering practical computational efficiency.

Skill-aware Mutual Information optimization enhances RL agent generalization across diverse tasks by distinguishing context embeddings based on skills, leading to improved zero-shot performance and ro…

Randomized sparse matrix compression boosts large-scale cancer radiotherapy optimization, improving treatment quality without sacrificing speed.

RadarOcc: Revolutionizing autonomous driving with robust 3D occupancy prediction using 4D imaging radar, overcoming limitations of LiDAR and camera-based approaches.

POETRY: a recursive neural theorem prover achieving 5.1% higher success rate and solving substantially longer proofs.

Novel metric space magnitude measures rigorously quantify the diversity of latent representations across multiple scales, showing superior performance in detecting mode collapse and characterizing emb…

This paper introduces a novel multi-stage generation framework for creating compositional scenes with fine-grained control by leveraging a trained diffusion model to produce individual scene component…

Unsupervised Articulated Object Modeling using Conditional View Synthesis learns pose and part segmentation from only two object observations, achieving significantly better performance than previous …