Biology-inspired brain model matches animal learning and reveals overlooked neuron activity

A new computational model of the brain based closely on its biology and physiology has not only learned a simple visual ...
Scientific Research Publishing

Reinforcement Learning for Antidepressant Dose Adjustment: An Explainable Agent Approach ()

Reinforcement Learning, Explainable AI, Computational Psychiatry, Antidepressant Dose Optimization, Major Depressive Disorder, Treatment Personalization, Clinical Decision Support Share and Cite: de ...
Scientific Research Publishing

Multimodal Digital Phenotyping for Bipolar Disorder: Robust Mood-State Classification and Early Relapse Risk Monitoring ()

Bipolar Disorder, Digital Phenotyping, Multimodal Learning, Face/Voice/Phone, Mood Classification, Relapse Prediction, T-SNE, Ablation Share and Cite: de Filippis, R. and Al Foysal, A. (2025) ...
IEEE

Context-Aware Graph Inference and Generative Adversarial Imitation Learning for Object-Goal Navigation in Unfamiliar Environment

Abstract: Object-goal navigation aims to guide an agent to find a specific target object in an unfamiliar environment based on first-person visual observations. It requires the agent to learn ...

Jing Zheng Explores Generative AI and Machine Learning Optimisation for Digital Advertising Efficiency

A generative advertising framework integrates diffusion models, multimodal learning, and brand style embeddings to automate creative ...
GitHub

Don’t Blind Your VLA: Aligning Visual Representations for OOD Generalization

To address the degradation of visual-language (VL) representations during VLA supervised fine-tuning (SFT), we introduce Visual Representation Alignment. During SFT, we pull a VLA’s visual tokens ...
Microsoft

LLM2CLIP: Powerful Language Model Unlocks Richer Visual Representation - Microsoft Research

CLIP is one of the most important multimodal foundational models today, aligning visual and textual signals into a shared feature space using a simple contrastive learning loss on large-scale ...
GitHub

MAC-VO: Metrics-aware Covariance for Learning-based Stereo Visual Odometry

We plan to release TensorRT accelerated implementation and adapting more matching networks for MAC-VO. If you are interested, please star ⭐ this repo to stay tuned. [Nov 2025] We release the ...
IEEE

InvSlotGNN: Unsupervised Discovery of Viewpoint Invariant Multiobject Representations and Visual Dynamics

Abstract: Learning multiobject dynamics purely from visual data is challenging due to the need for robust object representations that can be learned through robot interactions. In previous work ...