Adnan Saeed

Adnan Saeed is a deep learning researcher working on medical image analysis, with a focus on multimodal architectures, graph neural networks, and evidential deep learning for clinical imaging tasks. His peer reviewed research has appeared in journals across machine learning and biomedical signal processing. At AI Trend Blend he turns recent papers into clear, practical explainers, with an emphasis on what a method actually does and where it holds up, written for readers who want depth without the hype.

Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback.

Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback

Leave a Comment / Machine Learning, Cybersecurity, Federated Learning & AI Privacy, Math Applications /

Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback | AI Trend Blend AITrendBlend Machine Learning Computer Vision About Federated Learning · Journal of Machine Learning Research 26 (2025) 1–67 · 18 min read The Sampling Problem Federated Learning Has Been Ignoring — and How OSMD Finally Fixes It A multi-institution team […]

Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback Read More »

Memory Gym: Endless Tasks to Benchmark Memory Capabilities of Agents

Memory Gym: Endless Tasks to Benchmark Memory Capabilities of Agents

Leave a Comment / Agent Systems, Machine Learning /

Memory Gym: Endless Tasks to Benchmark Memory Capabilities of Agents | AI Trend Blend AITrendBlend Machine Learning Computer Vision Agent Systems About Deep Reinforcement Learning · Journal of Machine Learning Research 26 (2025) 1–40 · 22 min read When Memory Actually Matters: How Memory Gym’s Endless Tasks Expose What Benchmarks Have Been Missing All Along

Memory Gym: Endless Tasks to Benchmark Memory Capabilities of Agents Read More »

PEGN: How Persistent Homology Breaks the WL Barrier in Graph Neural Networks.

PEGN: How Persistent Homology Breaks the WL Barrier in Graph Neural Networks

Leave a Comment / Computer Vision, Machine Learning /

PEGN: How Persistent Homology Breaks the WL Barrier in Graph Neural Networks | AI Trend Blend Graph Learning · Journal of Machine Learning Research 26 (2025) 1–36 · 20 min read Loops, Cycles, and the Topology GNNs Cannot See: How PEGN Breaks the Weisfeiler-Lehman Ceiling A multi-institution team spanning Peking University, UC San Diego, Stony

PEGN: How Persistent Homology Breaks the WL Barrier in Graph Neural Networks Read More »

Why Your AI Says It's Confident When It Shouldn't Be — And How MaxWEnt Fixes It.

Why Your AI Says It’s Confident When It Shouldn’t Be — And How MaxWEnt Fixes It

Leave a Comment / Machine Learning, Math Applications, Optimization & Learning Theory /

Why Your AI Says It’s Confident When It Shouldn’t Be — And How MaxWEnt Fixes It | AI Trend Blend AITrendBlend Machine Learning Math Applications About Machine Learning Safety · Journal of Machine Learning Research 26 (2025) · Michelin & ENS Paris-Saclay · 18 min read Why Your AI Says It’s Confident When It Shouldn’t

Why Your AI Says It’s Confident When It Shouldn’t Be — And How MaxWEnt Fixes It Read More »

Sheffer Sequences With Zeros on a Line — A Hidden Bridge to the Riemann Zeta Function.

Sheffer Sequences With Zeros on a Line — A Hidden Bridge to the Riemann Zeta Function

Leave a Comment / Math Applications /

Sheffer Sequences With Zeros on a Line — A Hidden Bridge to the Riemann Zeta Function | AI Trend Blend AITrendBlend Mathematics Machine Learning About Pure Mathematics · Journal of Mathematical Analysis and Applications 563 (2026) · Sungkyunkwan University & California State University, Fresno · 14 min read Zeros in Perfect Formation — How a

Sheffer Sequences With Zeros on a Line — A Hidden Bridge to the Riemann Zeta Function Read More »

DisC2o-HD: Distributed Causal Inference with Covariate Shift for High-Dimensional Healthcare Data.

DisC2o-HD: Distributed Causal Inference with Covariate Shift for High-Dimensional Healthcare Data

Leave a Comment / Medical AI, Federated Learning & AI Privacy, Math Applications /

DisC2o-HD: Distributed Causal Inference with Covariate Shift for High-Dimensional Healthcare Data | AI Trend Blend AITrendBlend Healthcare AI Math Applications About Healthcare AI · Journal of Machine Learning Research 26 (2025) · Penn / Columbia / Cornell · 20 min read DisC2o-HD: How Researchers Are Solving the Privacy-Accuracy Trade-off in Multi-Hospital Causal Inference A team

DisC2o-HD: Distributed Causal Inference with Covariate Shift for High-Dimensional Healthcare Data Read More »

Controlling the Uncontrollable — Null Controllability for Degenerate Coupled Parabolic Equations.

Controlling the Uncontrollable — Null Controllability for Degenerate Coupled Parabolic Equations

Leave a Comment / Math Applications /

Controlling the Uncontrollable — Null Controllability for Degenerate Coupled Parabolic Equations | AI Trend Blend AITrendBlend Mathematics Machine Learning About Applied Mathematics · Journal of Mathematical Analysis and Applications 563 (2026) · UERJ, UPB, UFF & FAU Erlangen · 16 min read Controlling the Uncontrollable — How Mathematicians Are Steering Degenerate Heat Equations That Change

Controlling the Uncontrollable — Null Controllability for Degenerate Coupled Parabolic Equations Read More »

Singular p-Laplacian Problems: Existence, Uniqueness & Multiplicity via Variational Methods.

Singular p-Laplacian Problems: Existence, Uniqueness & Multiplicity via Variational Methods

Leave a Comment / Math Applications /

Singular p-Laplacian Problems: Existence, Uniqueness & Multiplicity via Variational Methods | AI Trend Blend AITrendBlend Machine Learning Math Applications About Mathematical Analysis · J. Math. Anal. Appl. 563 (2026) 130767 · 16 min read When Equations Break at Zero: A New Unified Theory for Singular p-Laplacian Problems Mathematicians Pasquale Candito, Giuseppe Failla, and Bruno Vassallo

Singular p-Laplacian Problems: Existence, Uniqueness & Multiplicity via Variational Methods Read More »

Two Generalizations of Stampacchia Lemma — Regularity Theory for Elliptic PDEs

Two Generalizations of Stampacchia Lemma — Regularity Theory for Elliptic PDEs

Leave a Comment / Math Applications /

Two Generalizations of Stampacchia Lemma — Regularity Theory for Elliptic PDEs | AI Trend Blend AITrendBlend Mathematics Machine Learning About Pure Mathematics · Journal of Mathematical Analysis and Applications 563 (2026) · Hebei University & UNC Charlotte · 18 min read Two Generalizations of Stampacchia Lemma — And Why They Make Regularity Theory Sharper Than

Two Generalizations of Stampacchia Lemma — Regularity Theory for Elliptic PDEs Read More »

Multimodal AI 2026: ChatGPT 5.5, Claude Opus 4.7 & Gemini Pro 3.1 Compared.

Multimodal AI 2026: ChatGPT 5.5, Claude Opus 4.7 & Gemini Pro 3.1 Compared

Leave a Comment / Prompt Engineering, Anthropic Claude, ChatGPT, Google Gemini, Multimodal AI /

Multimodal AI 2026: ChatGPT 5.5, Claude Opus 4.7 & Gemini Pro 3.1 Compared AI Model Comparison · Multimodal Multimodal AI in 2026: ChatGPT 5.5, Claude Opus 4.7 & Gemini Pro 3.1 Compared ChatGPT 5.5 Claude Opus 4.7 Gemini Pro 3.1 Multimodal AI Model Comparison 2026 aitrendblend.com Updated May 2026 16 min read Priya had three

Multimodal AI 2026: ChatGPT 5.5, Claude Opus 4.7 & Gemini Pro 3.1 Compared Read More »