5 best record players, reviewed by an audio expert
the-independent.com·18h
🕯️Wax Cylinders
Building a Plain Seq2Seq Model for Language Translation
machinelearningmastery.com·6h
📝Text Compression
This Beats Pill Speaker Is on Sale for $90 Right Now
lifehacker.com·10h
💿FLAC Archaeology
We're building cross-functional AI-native teams (Would love your feedback)
medium.com·10h·
Discuss: Hacker News
🔄Language Evolution
FOCUS: Fused Observation of Channels for Unveiling Spectra
arxiv.org·4h
🧠Machine Learning
Machine Learning Fundamentals: ensemble learning with python
dev.to·1d·
Discuss: DEV
🌊Stream Processing
DIVER-0 : A Fully Channel Equivariant EEG Foundation Model
arxiv.org·4h
📊Learned Metrics
Machine Learning Fundamentals: ensemble learning tutorial
dev.to·1d·
Discuss: DEV
🌊Stream Processing
H-Nets – The Past
goombalab.github.io·1d·
Discuss: Hacker News
🧠Machine Learning
Enhancing Generalization in PPG-Based Emotion Measurement with a CNN-TCN-LSTM Model
arxiv.org·4h
🧠Neural Codecs
Early Detection of Furniture-Infesting Wood-Boring Beetles Using CNN-LSTM Networks and MFCC-Based Acoustic Features
arxiv.org·4d
🎧Learned Audio
The calculus of variations of the Transformer on the hyperspherical tangent bundle
arxiv.org·4h
🌀Differential Geometry
Temporal Basis Function Models for Closed-Loop Neural Stimulation
arxiv.org·4h
⚡Effectful Programming
Procedure Learning via Regularized Gromov-Wasserstein Optimal Transport
arxiv.org·4h
🧠Machine Learning
Top 5 AI Applications in Modern Work Environments
dev.to·22h·
Discuss: DEV
🌊Stream Processing
FedMultiEmo: Real-Time Emotion Recognition via Multimodal Federated Learning
arxiv.org·4h
🧠Machine Learning
Depthwise-Dilated Convolutional Adapters for Medical Object Tracking and Segmentation Using the Segment Anything Model 2
arxiv.org·4h
🌀Hyperbolic Geometry
Beyond the Migration: Optimizing Legacy Code for AI Performance & Scalability
dev.to·1d·
Discuss: DEV
🌊Streaming Systems
Kolmogorov Arnold Networks (KANs) for Imbalanced Data -- An Empirical Perspective
arxiv.org·1d
🧠Machine Learning
Mixture of Autoencoder Experts Guidance using Unlabeled and Incomplete Data for Exploration in Reinforcement Learning
arxiv.org·4h
🧠Machine Learning