DMC

A Diffusion Monte Carlo algorithm employing depth first traversal and a stack instead of a swarm

arXiv:2606.08946v1 Announce Type: cross Abstract: Diffusion Monte Carlo (DMC) and Monte Carlo for particle transport with importance sampling both involve simulations of weighted walkers that undergo birth and death processes (splitting and Russian Roulette). The established implementations of these methods are quite different: Particle simulation Monte Carlo employs a stack to handle the splitting history whereas in traditional DMC one follows a swarm of walkers. The particle simulation...

Rank-Constrained Deep Matrix Completion for Group Recommendation

new Abstract: The growing popularity of group activities has increased the need for methods that provide recommendations to groups of users given their individual preferences. Many existing group recommender systems rely on aggregating individual user preferences, but they often struggle with high-dimensional and highly sparse rating data commonly found in real-world scenarios. We propose Group Rank-Constrained Deep Matrix Completion (Group RC-DMC), a novel framework that extends RC-DMC by...

Coke can hair rollers and Puerto Rican pride: the street photography of Janette Beckman – in pictures

Four decades of Janette Beckman’s images will be on view until 18 April 2027 at Seattle’s Museum of Pop Culture (MoPOP). The exhibit Rebels + Icons: The Photography of Janette Beckman will feature 700-plus archival and newly taken images. Among many iconic photographs, Beckman is known for photographing musical legends like Salt-N-Pepa and Run-DMC, and her striking approach to street photography Continue reading...

UK petrol station plunges into liquidation after serving community for nine years

UK petrol station plunges into liquidation after serving community for nine years Motorists across the globe have felt the pinch of higher fuel prices after ran closed the critical Strait of Hormuz - through which 20% of global oil traded passes A UK petrol station has plunged into administration after serving a historic town for nine years. HD Food and Fuel Ltd have been appointed Andrew Mark Bland of DMC Recovery Limited to oversee the liquidation of the business. Liquidation is the legal...

Reinforcement Learning from Cross-domain Videos with Video Prediction Model

arXiv:2606.03201v2 Announce Type: replace Abstract: Reinforcement learning from expert videos across visually distinct domains is challenging due to the absence of reward signals and the presence of domain gaps. We introduce XIPER (Cross-domain Video Prediction Reward), a reward model for learning from expert videos collected in a visually different domain, where the agent's appearance differs due to factors such as color, morphology, or the sim-to-real gap. More specifically, XIPER trains a...

Reinforcement Learning from Cross-domain Videos with Video Prediction Model

arXiv:2606.03201v1 Announce Type: new Abstract: Reinforcement learning from expert videos across visually distinct domains is challenging due to the absence of reward signals and the presence of domain gaps. We introduce XIPER (Cross-domain Video Prediction Reward), a reward model for learning from expert videos collected in a visually different domain, where the agent's appearance differs due to factors such as color, morphology, or the sim-to-real gap. More specifically, XIPER trains a...

Coke can hair rollers and Puerto Rican pride: the street photography of Janette Beckman – in pictures

DecepGPT: Schema-Driven Deception Detection with Multicultural Datasets and Robust Multimodal Learning

arXiv:2603.23916v3 Announce Type: replace Abstract: Multimodal deception detection aims to identify deceptive behavior by analyzing audiovisual cues for forensics and security. In these high-stakes settings, investigators need verifiable evidence connecting audiovisual cues to final decisions, along with reliable generalization across domains and cultural contexts. However, existing benchmarks provide only binary labels without intermediate reasoning cues.

Unlocking feedforward capabilities in Model Predictive Control algorithms to deal with measurable disturbances

Announce Type: new Abstract: Disturbance rejection is a central objective in process control, particularly when measurable disturbances can be exploited through feedforward action. Although Model Predictive Control (MPC) naturally incorporates disturbance models and prediction capabilities, standard formulations cannot achieve complete disturbance rejection since the cost function penalises control effort.