Search: “tutorials”

arXiv:2508.00937v4 Announce Type: replace-cross Abstract: We present a general approach to visualizing uncertainty in static 2-D statistical graphics. If we treat a visualization as a function of its

arXiv:2607.01029v1 Announce Type: new Abstract: Collaborative capture of dynamic targets is common in nature as an essential strategy for weaker species against the strong. Similar concepts have shown

arXiv:2607.00140v1 Announce Type: cross Abstract: As computing education expands beyond traditional programming into operational domains such as systems administration and command-line environments, e

arXiv:2607.00321v1 Announce Type: new Abstract: Reconstructing high-fidelity 3D models of highly articulated animals, such as dogs, from a single in-the-wild image remains a formidable challenge. In t

arXiv:2607.00581v1 Announce Type: new Abstract: Sparse tangent portfolio optimization aims to learn an interpretable, low-cardinality portfolio in the tangency direction of the mean-variance frontier.

arXiv:2607.00720v1 Announce Type: cross Abstract: Despite the increasing sophistication of industrial AI systems, the ability to reliably detect subtle and noisy anomalies in complex time series data

arXiv:2607.00947v1 Announce Type: new Abstract: Generative models learn data distributions that reside on a low-dimensional manifold within a higher-dimensional ambient space. Optimizing differentiabl

arXiv:2607.00183v1 Announce Type: new Abstract: Adapting pre-trained text-to-image diffusion models, whether to learn new visual concepts or erase unwanted ones, is routinely evaluated on its intended

arXiv:2607.00320v1 Announce Type: cross Abstract: We establish approximation and learning guarantees for Fourier neural operators (FNOs) applied to time-T solution operators of dissipative evolution e

arXiv:2603.26661v2 Announce Type: replace Abstract: Most recent advances in 3D generative modeling rely on diffusion or flow-matching formulations. We instead explore a fully autoregressive alternativ

arXiv:2607.01012v1 Announce Type: new Abstract: Data assimilation models state dynamics conditioned on sequential observations, and has wide-ranging scientific applications. In the filtering setting,

arXiv:2607.00301v1 Announce Type: new Abstract: The emergence of powerful deep generative models based on diffusion and flow matching has enabled the learning and modeling of complex distributions. Le

arXiv:2607.00492v1 Announce Type: new Abstract: We introduce GenSP, a data-driven framework that learns consistent spherical parameterizations across a collection of genus-0 shapes. Instead of optimiz

arXiv:2602.03082v2 Announce Type: replace Abstract: A growing number of neural architectures have been proposed to enforce geometric constraints, including projection-based networks, exponential-map u

arXiv:2607.00083v1 Announce Type: cross Abstract: Language models have changed from unreliable text generators to highly-capable large models with trillions of parameters. Capability increases come ha

Hot take: I think it's still important to understand the code that our agents write! In this mega thread (based on my AIE talk today), I will explain why that's the case, and show some ideas for how t

huge week of really exciting launches at langchain! big week at langchain, with a lot of launches: 1/ OpenWiki - auto generate a wiki of a github repo 2/ two different voice agent tutorials 3/ Harbor

arXiv:2403.19645v2 Announce Type: replace Abstract: The rapid advancement of diffusion models has enabled the generation of high-fidelity images from textual prompts, yet achieving precise, disentangl

arXiv:2607.00955v1 Announce Type: cross Abstract: Implicit neural representations (INRs) are well suited to cardiac motion estimation, providing continuous, compact representations of motion fields. H

arXiv:2602.23164v2 Announce Type: replace Abstract: Foundation models must handle multiple generative processes, yet mechanistic interpretability largely studies capabilities in isolation; it remains

arXiv:2607.01124v1 Announce Type: cross Abstract: Muon has recently emerged as one of the most effective optimizers for training large neural networks, yet its empirical success has been explained fro

New research from Google. LLMs hallucinate with high confidence, miss their own knowledge boundaries, and misreport uncertainty. Most fixes bolt calibration on from the outside. RLMF turns the model o

Obvious in retrospect, but I didn't really anticipate: Fable: Performing Final Review of <Awesome Feature> Also Fable: I appear to have introduced a critical security vulnerability. <This model's safe

arXiv:2607.00586v1 Announce Type: cross Abstract: We present a simple, yet general approach to study the scaling properties as the dimensionality of Metropolised MCMC sampling algorithms increases. Th

Our goal is to help security teams shift from reactive triage to proactively fixing what matters, close the critical gaps scanners miss before they become breaches, and return engineering capacity to

arXiv:2607.00522v1 Announce Type: new Abstract: Restoring incomplete or damaged 3D objects is crucial for cultural heritage preservation, occluded object reconstruction, and artistic design. Existing

arXiv:2607.00714v1 Announce Type: cross Abstract: Self-conditioning is a core technique that enhances continuous flow-based language models, where the model learns to denoise generated text by conditi

arXiv:2509.22557v3 Announce Type: replace Abstract: Mixed bundle pricing is a classic revenue management problem arising in industries such as e-commerce, tourism, and video games. It refers to design

arXiv:2607.01105v1 Announce Type: new Abstract: We present SynLaD, a latent diffusion framework for small-molecule generation that unifies ligand-based drug design objectives (what to make) with synth

arXiv:2607.00849v1 Announce Type: new Abstract: News articles are an important source of information on disaster impacts and adaptation. A key methodological challenge in socio-environmental studies i

In this post, we demonstrate how to deploy BoltzGen on SageMaker AI and run an end-to-end protein design experiment. By the end of the walkthrough, you have a working setup that scales from quick vali

arXiv:2606.31069v1 Announce Type: new Abstract: Up to this point, keyword extraction task typically relies solely on textual data. Neglecting visual details and audio features from image and audio mod

arXiv:2606.31275v1 Announce Type: cross Abstract: Online Continual Self-Supervised Learning (OCSSL) aims to learn representations from a continuous stream of unlabeled data, without knowledge of task

arXiv:2606.31909v1 Announce Type: new Abstract: In this work, we study Compositional Dexterous Functional Object Manipulation (CD-FOM): tasks such as aiming and actuating a spray bottle on a plant or

arXiv:2606.15305v2 Announce Type: replace Abstract: Accurate brain tumor segmentation from multiparametric magnetic resonance imaging (MRI) is critical for treatment planning, response assessment, and

arXiv:2510.09340v2 Announce Type: replace Abstract: Recent language models exhibit significant logical reasoning abilities, yet the mechanisms supporting deductive inference remain poorly understood.

Trq212 is presenting a Field Guide to Fable at AI.Engineer World's Fair, indicating renewed interest or development in the Fable project or framework. This presentation likely covers Fable's features,

arXiv:2606.32016v1 Announce Type: new Abstract: Multimodal graph foundation models aim to learn reusable knowledge from graphs enriched with text, images, attributes, and relational topology, thereby

arXiv:2512.04390v2 Announce Type: replace-cross Abstract: Joint video super-resolution and deblurring (VSRDB) requires both efficient long-range temporal modeling and robustness to frame-wise exposure

At Google Cloud, we are committed to providing public sector organizations around the globe with cloud technology that is highly flexible, scalable, and built with market-leading standards for data pr

Great talk by @trq212 ! You mentioned you generated the slides in 4 hours with Fable? These slides were gorgeous!! Most other presenters using AI generated deck look horrible. Can you please share any

In this post, we demonstrate how to implement HippoRAG using a comprehensive AWS stack. We use Amazon Bedrock for LLM capabilities, Amazon Neptune for graph database functionality, Amazon Neptune Anal

arXiv:2606.32009v1 Announce Type: new Abstract: Vision-language-action (VLA) models across robot embodiments require high-quality observation--action supervision to learn deployable action distributio

This Replit post likely provides a security walkthrough covering four essential security considerations for developers building applications on the Replit platform. The guide appears aimed at app buil

arXiv:2505.18521v2 Announce Type: replace Abstract: The substantial training cost of diffusion models hinders their deployment. Immiscible Diffusion recently showed that reducing diffusion trajectory

arXiv:2606.31924v1 Announce Type: new Abstract: Controllable image generation methods, such as ControlNet, have demonstrated a remarkable capacity to introduce visual conditions(e.g., depth maps) to g