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Release: scan-for-secrets 0.2 CLI tool now streams results as they are found rather than waiting until the end, which is better for large directories. -d/–directory option can now be used multiple times to scan multiple directories. New -f/–file option for specifying one or more individual files to scan. New scan_directory_iter(), scan_file() and scan_file_iter() Python API functions. New -v/–verbose option which shows each directory that is being scanned.

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Release: scan-for-secrets 0.1 I like publishing transcripts of local Claude Code sessions using my claude-code-transcripts tool but I’m often paranoid that one of my API keys or similar secrets might inadvertently be revealed in the detailed log files. I built this new Python scanning tool to help reassure me. You can feed it secrets and have it scan for them in a specified directory: uvx scan-for-secrets $OPENAI_API_KEY -d logs-to-publish/ If you leave off the -d it defaults to […]

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In many modern applications, a carefully designed primary study provides individual-level data for interpretable modeling, while summary-level external information is available through black-box, efficient, and nonparametric machine-learning predictions. Although summary-level external information has been studied in the data integration literature, there is limited methodology for leveraging external nonparametric machine-learning predictions to improve statistical inference in the primary study. We propose a general empirical-likelihood framework that incorporates external predictions through moment constraints. An advantage of nonparametric machine-learning prediction is […]

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Model-free deep reinforcement learning (DRL) methods suffer from poor sample efficiency. To overcome this limitation, this work introduces an adaptive reduced-order-model (ROM)-based reinforcement learning framework for active flow control. In contrast to conventional actor–critic architectures, the proposed approach leverages a ROM to estimate the gradient information required for controller optimization. The design of the ROM structure incorporates physical insights. The ROM integrates a linear dynamical system and a neural ordinary differential equation (NODE) for estimating the nonlinearity in […]

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Release: research-llm-apis 2026-04-04 I’m working on a major change to my LLM Python library and CLI tool. LLM provides an abstraction layer over hundreds of different LLMs from dozens of different vendors thanks to its plugin system, and some of those vendors have grown new features over the past year which LLM’s abstraction layer can’t handle, such as server-side tool execution. To help design that new abstraction layer I had Claude Code read through the Python client libraries […]

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Multi-task representation learning (MTRL) is an approach that learns shared latent representations across related tasks, facilitating collaborative learning that improves the overall learning efficiency. This paper studies MTRL for multi-task reinforcement learning (RL), where multiple tasks have the same state-action space and transition probabilities, but different rewards. We consider T linear Markov Decision Processes (MDPs) where the reward functions and transition dynamics admit linear feature embeddings of dimension d. The relatedness among the tasks is captured by a […]

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I’ve open-sourced GS-DroneGym, a drone-first research stack for vision-language-action work. Main idea: instead of only using synthetic assets, it can render observations from 3D Gaussian Splatting scenes, so you can prototype aerial waypoint policies in environments much closer to real visual conditions. Current features: – 6-DOF quadrotor dynamics – waypoint controller for [x, y, z, yaw] – gsplat renderer with CPU fallback – navigation tasks: PointNav, ObjectNav, ObstacleSlalom, DynamicFollow, NarrowCorridor – live viewer with RGB / depth / […]

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Federated learning (FL) enables multiple clients to collaboratively train a global machine learning model via a server without sharing their private training data. In traditional FL, the system follows a synchronous approach, where the server waits for model updates from numerous clients before aggregating them to update the global model. However, synchronous FL is hindered by the straggler problem. To address this, the asynchronous FL architecture allows the server to update the global model immediately upon receiving any […]

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I’ve open-sourced GS-DroneGym, a drone-first research stack for vision-language-action work. Main idea: instead of only using synthetic assets, it can render observations from 3D Gaussian Splatting scenes, so you can prototype aerial waypoint policies in environments much closer to real visual conditions. Current features: – 6-DOF quadrotor dynamics – waypoint controller for [x, y, z, yaw] – gsplat renderer with CPU fallback – navigation tasks: PointNav, ObjectNav, ObstacleSlalom, DynamicFollow, NarrowCorridor – live viewer with RGB / depth / […]

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