failure-modes

ML Approaches for RUL Prediction, Anomaly Detection, Survival Analysis and Failure Classification

Physics-informed neural networks for highly compressible flows 🧠🌊

Collection of how and why software systems fail

RMC-TotalRisk is a powerful risk analysis software package designed to support dam and levee safety investment decisions.

[UAI 2023] Official implementation of Efficient Failure Pattern Identification of Predictive Algorithms

Detecting Failure Modes in Image Reconstructions with Interval Neural Network Uncertainty

Enabling Model-Based Diagnosis and Failure Model Generation with Active Automata Learning

What breaks after an AI agent team keeps running, and the runtime layer needed to recover.

Empirical benchmark comparing agent architectures (single-agent, multi-agent, adaptive) on ProgramDev-v0 and CyberGym tasks. Key finding: adaptive architecture > single-agent > fixed-pipeline multi-agent.

Source-available, measurement-first pulsed-energy testbed for tri-sector storage/discharge control, derated storage, phase authority, sensor-truth checks, energy accounting, kill criteria, evidence bundles, and human-reviewed scale-up gates.

PressureX is an engineering evaluation package for a passive layered structural mitigation concept using shear-thickening fluid behavior to broaden impulsive loads and reduce peak transmitted response in high-vibration aerospace structures. Targets are design-intent until validated.

Architecture for resilient, governed, and regenerative intelligence under uncertainty.

Runtime-agnostic hook harness that catches unverifiable prompts, enforces failure-mode templates, and gates task completion on passing tests.

A practical library of failure modes in AI workflows, automation, and production systems.

WorldLag — Agent Failure Series #9. Interactive simulator of stale world model / belief-reality divergence in AI agents.

A systems-first implementation of agent control: explicit retrieval decisions, planner–executor separation, and auditable memory as core architectural mechanisms.

Open dataset for AI agent evaluation: failure modes, patterns, use cases, glossary, ecosystem tools, protocols, and research. 404 structured entries.

A systems-level analysis of static RAG pipelines, isolating ingestion, retrieval, and ranking boundaries to expose structural failure modes before generation.

Explicit control and observability over when an LLM should answer, hedge, or refuse — treating generation as a governed system layer, not a side effect of retrieval.