omlx.ai
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Rememberbox Reader
Your quiet, text-first reading library.
2026-04-01
2026-03-31
doi.org
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2026-03-30
GitHub - lucascrespo23/pinch-type: Pinch to zoom text, not the page. Built on @chenglou/pretext.
Pinch to zoom text, not the page. Built on @chenglou/pretext. - lucascrespo23/pinch-type
Inside Ohm's PEG-to-Wasm compiler | Ohm
Ohm is a user-friendly parsing toolkit for JavaScript and TypeScript. You can use it to parse custom file formats or quickly build parsers, interpreters, and compilers for programming languages. Learn more
2026-03-29
GitHub - meagmohit/EEG-Datasets: A list of all public EEG-datasets
A list of all public EEG-datasets. Contribute to meagmohit/EEG-Datasets development by creating an account on GitHub.
2026-03-28
Partially observable Markov decision process
A partially observable Markov decision process (POMDP) is a generalization of a Markov decision process (MDP). A POMDP models an agent decision process in which it is assumed that the system dynamics are determined by an MDP, but the agent cannot directly observe the underlying state. Instead, it must maintain a sensor model (the probability distribution of different observations given the underlying state) and the underlying MDP. Unlike the policy function in MDP which maps the underlying state
2026-03-27
aidemos.atmeta.com
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Learning Enhanced Ensemble Filters
The filtering distribution in hidden Markov models evolves according to the law of a mean-field model in state-observation space. The ensemble Kalman filter (EnKF) approximates this mean-field model with an ensemble of interacting particles, employing a Gaussian ansatz for the joint distribution of the state and observation at each observation time. These methods are robust, but the Gaussian ansatz limits accuracy. Here this shortcoming is addressed by using machine learning to map the joint pre
High Dimensional Ensemble Kalman Filter
The Ensemble Kalman Filter (EnKF), as a fundamental data assimilation approach, has been widely used in many fields of the sciences and engineering. When the state variable is of high dimensional accompanied with high resolution observations of physical models, some key theoretical aspects of the EnKF are open for investigation. This paper proposes several high dimensional EnKF (HD-EnKF) methods equipped with consistent estimators for the important forecast error covariance and Kalman Gain matri
Ensemble Kalman filter
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Using Data Assimilation for Quantitative Electroencephalography Analysis - PubMed
We propose a method based on the ensemble Kalman filter (EnKF) together with quantitative electroencephalogram (QEEG) coherence and power spectrum analysis for evaluating changes in brain activity associated with cognitive processes. Such analysis framework has been widely used in the context of dat …
Quantitative electroencephalography
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jmpcr.samipubco.com
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2026-03-26
Vector Symbolic Algebras for the Abstraction and Reasoning Corpus
The Abstraction and Reasoning Corpus for Artificial General Intelligence (ARC-AGI) is a generative, few-shot fluid intelligence benchmark. Although humans effortlessly solve ARC-AGI, it remains extremely difficult for even the most advanced artificial intelligence systems. Inspired by methods for modelling human intelligence spanning neuroscience to psychology, we propose a cognitively plausible ARC-AGI solver. Our solver integrates System 1 intuitions with System 2 reasoning in an efficient and
2026-03-25
www.sciencedirect.com
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github.com
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Your bridge to wealth is being pulled up
For two centuries, the credential system gave intelligence a route to heritable capital. Artificial intelligence is closing that route. This essay builds the argument from first principles - with probability theory, interactive simulations, and a prediction specific enough to be falsifiable - and puts a number on the window that remains.
LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels
Joint Embedding Predictive Architectures (JEPAs) offer a compelling framework for learning world models in compact latent spaces, yet existing methods remain fragile, relying on complex multi-term losses, exponential moving averages, pre-trained encoders, or auxiliary supervision to avoid representation collapse. In this work, we introduce LeWorldModel (LeWM), the first JEPA that trains stably end-to-end from raw pixels using only two loss terms: a next-embedding prediction loss and a regularize
TurboQuant: Redefining AI efficiency with extreme compression
Vectors are the fundamental way AI models understand and process information. Small vectors describe simple attributes, such as a point in a graph, while “high-dimensional” vectors capture complex information such as the features of an image, the meaning of a word, or the properties of a dataset. High-dimensional vectors are incredibly powerful, but they also consume vast amounts of memory, leading to bottlenecks in the key-value cache, a high-speed "digital cheat sheet" that stores frequently u
2026-03-24
Main Page - Algorithms for Competitive Programming
The goal of this project is to translate the wonderful resource http://e-maxx.ru/algo which provides descriptions of many algorithms and data structures especially popular in field of competitive programming. Moreover we want to improve the collected knowledge by extending the articles and adding new articles to the collection.
Stable End-to-End Joint-Embedding Predictive Architecture from Pixels
End-to-end joint-embedding predictive architecture from pixels.
2026-03-22
Taxicab geometry
From Wikipedia, the free encyclopedia
Doubly connected edge list
From Wikipedia, the free encyclopedia
HeroUI v3 (Previously NextUI) - Beautiful by default, customizable by design.
Beautiful, accessible React UI components built on React Aria and Tailwind CSS v4. The modern alternative to MUI, Chakra UI, and shadcn/ui for building production-ready applications.
Stop Writing Dead Programs, Strange Loop 2022
00:12.95 My talk today is Stop Writing Dead Programs.