Audiovisual Fulldome Performance by MONOCOLOR (Marian Essl) at SAT Montreal (Société des arts technologiques). In Latent Space, fine lines weave virtual…
Abstract page for arXiv paper 2204.12530: Expanding the Latent Space of StyleGAN for Real Face Editing
We propose a strategy for optimizing physical quantities based on exploring in the latent space of a variational autoencoder (VAE). We train a VAE model using various spin configurations formed on a two-dimensional chiral magnetic system. Three optimization algorithms are used to explore the latent space of the trained VAE. The first algorithm, the single-code modification algorithm, is designed for improving the local energetic stability of spin configurations to generate physically plausible spin states. The other two algorithms, the genetic algorithm and the stochastic algorithm, aim to optimize the global physical quantities, such as topological index, magnetization, energy, and directional correlation. The advantage of our method is that various optimization algorithms can be applied in the latent space containing the abstracted representation constructed by the trained VAE model. Our method based on latent space exploration is utilized for efficient physical quantity optimization.
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HVAC- Practical Basic Calculation.pdf - Free download as PDF File (.pdf), Text File (.txt) or read online for free.
AI and Coding Software for kids to learn Block-based coding and Python Programming. Kids can make innovative AI, ML, IoT, and Robotics Projects.
Figure 1. Heat transfer in a warm climate greenhouse. QR is solar radiation, QG is convection and conduction across the greenhouse cladding material, QV is the heat transfer via air exchange by ventilation, QS is the heat transfer to and from the soil, QP is the heat transfer to and from the plants and other greenhouse components such as irrigation systems, and QL is the latent heat transferred to water in evaporative cooling systems, in this case a fog or mist system. - "The natural ventilation augmented cooling (NVAC) greenhouse: design development, analysis of greenhouse climate, and plant response"
✨🔬 A flexible diffraction simulator for exploring and visualizing physical optics. - rafael-fuente/diffractsim
Marble Run designed by Aurelien Malagoli. Connect with them on Dribbble; the global community for designers and creative professionals.
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Latent space interpolations
Found this beautiful latent space in Midjourney. Excited to start trying StableDiffusion.
Talent Latent was a ‘15 in 1’ photography exhibition that presented the work of 15 photographers in one space. The catalogue mirrors this ‘15 in 1’ format: it consists of 15 booklets (one per artist), plus one for institutional texts and articles by the c…
Translucent polychromatic forests. AI-rendered from Midjourney’s latent space. #midjourneyarchitecture #ArchDaily #diffusion_architecture… | Instagram
Computer made designs and sketches for generative design exploring form finding in latent space #ai #designinspo #latentspace #generativeart
With encapsulation of your crawl space, you will also be able to block the entry of insects and rodents and ease the latent load on your HVAC system
Mapping behavioural actions to neural activity is a fundamental goal of neuroscience. As our ability to record large neural and behavioural data increases, there is growing interest in modelling neural dynamics during adaptive behaviours to probe neural representations1–3. In particular, although neural latent embeddings can reveal underlying correlates of behaviour, we lack nonlinear techniques that can explicitly and flexibly leverage joint behaviour and neural data to uncover neural dynamics3–5. Here, we fill this gap with a new encoding method, CEBRA, that jointly uses behavioural and neural data in a (supervised) hypothesis- or (self-supervised) discovery-driven manner to produce both consistent and high-performance latent spaces. We show that consistency can be used as a metric for uncovering meaningful differences, and the inferred latents can be used for decoding. We validate its accuracy and demonstrate our tool’s utility for both calcium and electrophysiology datasets, across sensory and motor tasks and in simple or complex behaviours across species. It allows leverage of single- and multi-session datasets for hypothesis testing or can be used label free. Lastly, we show that CEBRA can be used for the mapping of space, uncovering complex kinematic features, for the production of consistent latent spaces across two-photon and Neuropixels data, and can provide rapid, high-accuracy decoding of natural videos from visual cortex. A new encoding method, CEBRA, jointly uses behavioural and neural data in a (supervised) hypothesis- or (self-supervised) discovery-driven manner to produce both consistent and high-performance latent spaces.
Researchers from MIT CSAIL predict semantically meaningful and calibrated uncertainty intervals in the latent space of a generative adversarial network to know the exact limits in our ability to clean up, and reconstruct, partly blurred images.
