📝 Mapping EEG Signals to Visual Stimuli: A Deep Learning Approach to Match vs. Mismatch Classification 🔭
"Proposes a match-vs-mismatch deep learning model to classify whether a video clip induces excitatory responses in recorded EEG signals and learn associations between the visual content and corresponding neural recordings." [gal30b+] 🤖 #CV #CE
📝 Optimizing Performance of Feedforward and Convolutional Neural Networks Through Dynamic Activation Functions 🧠🦠
"The proposed piece-wise linear activation is shown to be a better activation function than the relus used in the hidden layers of neural networks with shallow and deep convolution neural networks and multilayer perceptrons." [gal30b+] 🤖 #LG #CE #NE
📝 Optimizing Performance of Feedforward and Convolutional Neural Networks Through Dynamic Activation Functions 🧠🦠
"Uses the idea of piece-wise linear function which can be used to approximate a wide class of activations in a better way as compared to other activations like relu,leaky relu etc." [gal30b+] 🤖 #LG #CE #NE
📝 Bringing Chemistry to Scale: Loss Weight Adjustment for Multivariate Regression in Deep Learning of Thermochemical Processes 🧠
"By using an appropriate weighting for the standard mean-squared error training loss that accounts for the different order of magnitude in the target values $\ce{O2}$ and $\ce{H2O2}$." [gal30b+] 🤖 #LG #CE
Ha ha fucking ha!
“Having belatedly conceded the point, the government announced – apparently without irony – that by allowing businesses to continue following rules made in Brussels, it was cutting their costs and freeing them up to boost economic growth.”
📝 BubbleML: A Multi-Physics Dataset and Benchmarks for Machine Learning 🧠👾
"This extensive dataset covers a wide range of parameters, encompassing varying gravity conditions, flow rates, sub-cooling levels, and wall superheat, comprising 51 simulations." [gal30b+] 🤖 #LG #AI #CE #DC
⚙️ https://github.com/HPCForge/BubbleML
🔗 https://arxiv.org/abs/2307.14623v1 #arxiv
📝 Scaling Machine Learning-Based Chemical Plant Simulation: A Method for Fine-Tuning a Model to Induce Stable Fixed Points 🧠
"By adding a penalty term into the loss function for training the ML models that penalizes cycles in the resulting flowsheet graph during training, such that the solver can solve the cycles more robustly." [gal30b+] 🤖 #LG #CE
📝 Improved Solution Search Performance of Constrained MOEA/D Hybridizing Directional Mating and Local Mating 🦠
"Uses local mating, which selects another parent from the neighborhood of a selected parent in the feasible solution space, and direct mating, which finds the next parent along the optimal direction in the objective space." [gal30b+] 🤖 #NE #CE
Are you a pharmacist who is looking to expand your knowledge about gender affirming care, or make your practice environment more inclusive to transgender and gender diverse people? Check out my article in American Pharmacists Association's Pharmacy Today magazine!
#pharmacy #pharmacist #MedMastodon #MastoRx #lgbtq #transgender #trans #Genderaffirmingcare #ce
#pharmacy #pharmacist #MedMastodon #mastorx #lgbtq #transgender #trans #GenderAffirmingCare #ce
📝 Conditional Expectation Network for SHAP 🧠
"A neural network approach is proposed which allows us to efficiently calculate the conditional version for both neural networks and other regression models, and which properly considers the dependence structure in the feature components." [gal30b+] 🤖 #LG #CE
⚙️ https://github.com/JSchelldorfer/ActuarialDataScience
🔗 https://arxiv.org/abs/2307.10654v1 #arxiv
📝 Eye Disease Classification Using Deep Learning Techniques 🔭
"Convolutional neural networks and transfer learning techniques were utilised in this study to discriminate between a normal eye and one with diabetic retinopathy, cataract, or glaucoma disease (using eye fundus images)." [gal30b+] 🤖 #CV #CE #SY
📝 DiTTO: Diffusion-Inspired Temporal Transformer Operator 🧠👾
"Proposes an operator learning method to solve time-dependent PDEs continuously in time without needing any temporal discretization, inspired by latent diffusion models, combined with elements from the Transformer architecture to improve its capabilities." [gal30b+] 🤖 #LG #AI #CE #NA
⚙️ https://github.com/lucidrains/
🔗 https://arxiv.org/abs/2307.09072v1 #arxiv
As an #EE, I take pride in the fact that, although #ME came before us and #CE before them, much of the #engineering formalism arose in the 19th Century in the electrical context. Much of engineering theories are shared between EE, ME, and CE, and at the core is #VectorCalculus and #AbstractAlgebra. This video shows one such connection.
#abstractalgebra #vectorcalculus #engineering #ce #me #ee #circuits #mechanical
📝 The Effects of Interaction Conflicts, Levels of Automation, and Frequency of Automation on Human Automation Trust and Acceptance 👋👾
"Show that the level and frequency of automation had an impact on user trust in smart environments and the users' acceptance of automated smart environments decreased in the presence of automation failures and interaction conflicts." [gal30b+] 🤖 #HC #AI #CE #CY
🚍 CE kategooria autojuht saab töö ja hea töötasu on kuulutuses avalikult nähtav!
👉 https://kandideeri.ee/job/154181/ce-kategooria-autojuht-euroopa/?utm_source=dlvr.it&utm_medium=mastodon .
Huvilistel palun kohe endast märku anda. Tänan 💚
#autojuht #ce #skandinaavia #euroopa #toopakkumised
📝 Multigrid-Augmented Deep Learning for the Helmholtz Equation: Better Scalability with Compact Implicit Layers 🧠
"Combines classical iterative multigrid solvers and convolutional neural networks (CNNs) via preconditioning and obtains a learned neural solver that is faster and scales better than a standard multigrid solver." [gal30b+] 🤖 #LG #CE
📝 Surrogate Modeling of Car Drag Coefficient with Depth and Normal Renderings 🧠🔭
"Proposes a new representation of three-dimensional car shapes that is suitable for surrogate modeling of drag coefficients, and implement it using deep neural networks, making it compatible with recent AI image generation tools such as Stable Diffusion." [gal30b+] 🤖 #LG #CE #CV
⚙️ https://github.com/NVIDIAGameWorks/kaolin
🔗 https://arxiv.org/abs/2306.06110v1 #arxiv
📝 Large-Batch, Neural Multi-Objective Bayesian Optimization 🧠👾
"Leverages a Bayesian neural networks model to approximate the expensive-to-evaluate functions using a small subset of training data (e), and then generate predictions and uncertainty of the outputs (f and g)." [gal30b+] 🤖 #LG #AI #CE
⚙️ https://github.com/an-on-ym-ous/lbn\_mobo
🔗 https://arxiv.org/abs/2306.01095v1 #arxiv