The Tyee: RCMP Spent Record Amount to Protect CGL Pipeline Last Year https://thetyee.ca/News/2023/09/11/RCMP-Spending-on-CGL-Pipeline/ #bcnews #TheTyee - via @tyee@mstdn.ca #CGLpipelinepolicing #JohnRidsdale #CGLpipeline #RCMPC-IRG #Na'Moks #C-IRG

📝 CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra 🧠

"Provides a linear operator abstraction with compositional multiple dispatch rules, which can be used for automatic construction of memory and runtime efficient numerical algorithms in JAX and PyTorch, while also accommodating new objects, operations, and rules in downstream packages." [gal30b+] 🤖 #LG #NA

⚙️ https://github.com/wilson-labs/cola
🔗 https://arxiv.org/abs/2309.03060v1 #arxiv

📝 Polynomial-Model-Based Optimization for Blackbox Objectives 🧠

"Uses a surrogate model to approximate the objective function and a Bayesian optimization approach to select the next point to evaluate the objective function at and balance exploration and exploitation in an efficient way." [gal30b+] 🤖 #LG #NA

🔗 https://arxiv.org/abs/2309.00663v1 #arxiv

Anyone going to be attending the Charlotte, NC Cybersecurity Conference this Thursday the 7th? I will be coming in the night before. Let me know and we can meet up for a drink! #NA #ITM

Hey everyone! I'm Gregory and I'm a #VideoCreator on #tiktok and #youtube creating #entertainment and #inspirational content for those suffering from #addiction and #trauma. I make content for those people who need #help #navigatingchallenges in the #twelvesteps of #aa or #na.

I am also a #redeemed son of God with a #purpose for my #life and a #song of #praise in my soul. #godisgood and I #lovejesus.

📝 Multi-Fidelity Reduced-Order Surrogate Modeling 🧠

"The key idea is to generate a spatial basis by applying the classical proper orthogonal decomposition to high-fidelity solution snapshots, and approximate the dynamics of the reduced states - time-parameter-dependent expansion coefficients of the POD basis - using a multi-fidelity long-short term memory network." [gal30b+] 🤖 #LG #NA

🔗 https://arxiv.org/abs/2309.00325v1 #arxiv

What would you do if your child was struck with an incredibly rare disease? My friend #GingerIrvine and her husband founded a patient's advocacy organisation to fund research into the #Parkinsons-like disease #neuroacanthocytosis and support patients - like their daughter Alex - who live with #NA. Ginger's been recognised with a major award by the International Parkinson and Movement Disorder Society... its first recipient since Michael J Fox: https://www.mdscongress.org/2023-Awardees#public #rareDiseases #advocacy

📝 Holistic Processing of Colour Images Using Novel Quaternion-Valued Wavelets on the Plane 🔭

"A quaternion-valued function on a plane is a function \(f\colon\mathbb{R}^{2}\to\mathbb{R}^{3}\), i." [gal30b+] 🤖 #CV #NA

🔗 https://arxiv.org/abs/2308.16875v1 #arxiv

📝 Guaranteed Stable Quadratic Models and Their Applications in SINDy and Operator Inference 🧠

"Parameterizes the unknown operators of a dynamical system using a linear combination of basis functions (also known as dictionary) and then solve a constrained optimization problem to learn those parameters." [gal30b+] 🤖 #LG #NA

🔗 https://arxiv.org/abs/2308.13819v1 #arxiv

@adam and @Johncdvorak , I'm calling a #NA intervention. Much like in the past, when either producers or one of you have called one or the other out for overuse of words or phrase, for all things sane, please stop interrupting your clips by repeating a word from the clip while the clip is still playing. It was funny when it was an occasional thing, but its over done now.

📝 Machine Learning in Parameter Estimation of Nonlinear Systems 🧠

"The Huber loss function guides a neural network to estimate parameters from time series data by minimizing the Huber loss function between true and estimated trajectories, allowing the neural network to fine-tune the model's weights to accurately estimate the parameters." [gal30b+] 🤖 #LG #NA

🔗 https://arxiv.org/abs/2308.12393v1 #arxiv

📝 On-Manifold Projected Gradient Descent 🧠

"Novel samples are projected onto a class manifold in diffusion embedding space and transformed into semantically meaningful directions in the original input space using the Nystr\"{o}m approximation to the diffusion map." [gal30b+] 🤖 #LG #NA

🔗 https://arxiv.org/abs/2308.12279v1 #arxiv

He has to be a #NA producer.... Again, 🔥

Not a very fresh hook-up | Censura Chan https://censurachan.gumroad.com/l/pregodemons #ホラー #afkアリーナ #afkarena #ゾンビ #na-ra #へそ #死姦 #死姦 #セックス #sex

@adam In the last #NA @Johncdvorak proverbially asked "what is AI good for?" Working in the field my answer is:Not for anything we can do well like AGI tries,like any art.It is good for things we can envision but can't practically do.There it will lead to the next Industrial Revolution, AGI art&stuff not really. Example from my work - what it does (and I like to call it Machine Understanding, not to be confused with sentience) is analyze real time 8 dimensional "movie",making reliable diagnosis

📝 A Domain-Adaptive Physics-Informed Neural Network for Inverse Problems of Maxwell's Equations in Heterogeneous Media 🧠

"Proposes a domain-adaptive PINN (da-PINN) to solve inverse problems of Maxwell's equations in heterogeneous media, which has two parts: location parameter of media interface and domain-adaptive training strategy." [gal30b+] 🤖 #LG #NA

🔗 https://arxiv.org/abs/2308.06436v1 #arxiv

📝 Size Lowerbounds for Deep Operator Networks 🧠

"Deep Operator Networks are an increasingly popular paradigm for solving regression in infinite dimensions and hence solve families of PDEs in one shot using a Deep Neural Network (DNN)." [gal30b+] 🤖 #LG #CC #NA

🔗 https://arxiv.org/abs/2308.06338v1 #arxiv

📝 On the Optimal Expressive Power of ReLU DNNs and Its Application in Approximation with Kolmogorov Superposition Theorem 🧠

"Based on Kolmogorov Superposition Theorem which provides a way to approximate functions by superposition of continuous one-variable functions of the form $\sum_{k=1}^{2d+1}g(x_k)$." [gal30b+] 🤖 #LG #NA

🔗 https://arxiv.org/abs/2308.05509v1 #arxiv

📝 On the Optimal Expressive Power of ReLU DNNs and Its Application in Approximation with Kolmogorov Superposition Theorem 🧠

"We first constructively prove that any continuous piecewise linear functions on $[0,1]$, comprising $O(N^2L)$ segments, can be represented by ReLU DNNs with $L$ hidden layers and $N$ neurons per layer." [gal30b+] 🤖 #LG #NA

🔗 https://arxiv.org/abs/2308.05509v1 #arxiv

📝 Prompting in-Context Operator Learning with Sensor Data, Equations, and Natural Language 🧠

"Proposes a novel neural network architecture that is designed for multi-modal in-context operator learning and is based on a language-model-like architecture with a transformer-based encoder." [gal30b+] 🤖 #LG #NA

🔗 https://arxiv.org/abs/2308.05061v1 #arxiv