activity
20162025
most citedEdward: A library for probabilistic modeling, inference, and criticism

223 citations · 556 across the 23 of their papers we have counts for

collaborators

24 papers

cs.LG2025★ 1 cited

Vendi Information Gain for Active Learning and its Application to Ecology

Quan Nguyen, Adji Bousso Dieng

While monitoring biodiversity through camera traps has become an important endeavor for ecological research, identifying species in the captured image data remains a major bottlene…

cs.LG2025

Alternators With Noise Models

Mohammad R. Rezaei, Adji Bousso Dieng

Alternators have recently been introduced as a framework for modeling time-dependent data. They often outperform other popular frameworks, such as state-space models and diffusion…

cs.IT2025

Vendi Information Gain: An Alternative To Mutual Information For Science And Machine Learning

Quan Nguyen, Adji Bousso Dieng

In his 1948 seminal paper A Mathematical Theory of Communication that birthed information theory, Claude Shannon introduced mutual information (MI), which he called "rate of transm…

cs.LG2025

The Alpha-Alternator: Dynamic Adaptation To Varying Noise Levels In Sequences Using The Vendi Score For Improved Robustness and Performance

Mohammad Reza Rezaei, Adji Bousso Dieng

Current state-of-the-art dynamical models, such as Mamba, assume the same level of noisiness for all elements of a given sequence, which limits their performance on noisy temporal…

cs.CV2024★ 2 cited

Beyond Aesthetics: Cultural Competence in Text-to-Image Models

Nithish Kannen, Arif Ahmad, Marco Andreetto +5

Text-to-Image (T2I) models are being increasingly adopted in diverse global communities where they create visual representations of their unique cultures. Current T2I benchmarks pr…

cs.LG2024★ 1 cited

Constraint-Aware Diffusion Models for Trajectory Optimization

Anjian Li, Zihan Ding, Adji Bousso Dieng +1

The diffusion model has shown success in generating high-quality and diverse solutions to trajectory optimization problems. However, diffusion models with neural networks inevitabl…