Tag
#neural-networks
7 insights
- ai · arxiv/cs.LG · 4 min
Hyperbolic neural networks outperform Euclidean models in quantum simulations
Researchers demonstrate that Poincaré and Lorentz recurrent architectures consistently beat standard neural quantum states on many-body physics benchmarks.
Apr 28, 2026 Read → - ai · arxiv/cs.LG · 8 min
Neural Networks and ODEs Compute Primitive Recursion via Dynamics, Not Composition
Bournez proves recurrent ReLU networks, polynomial ODEs, and discrete maps all express primitive recursive functions through continuous-time trajectories rather than symbolic subroutine chaining.
Apr 28, 2026 Read → - ai · arxiv/cs.LG · 4 min
Neural networks unmix single Raman spectra without multiple samples
A brain-inspired deep learning model solves the underdetermined problem of identifying chemical components from one noisy mixed spectrum, enabling rapid substance detection.
Apr 27, 2026 Read → - ai · arxiv/cs.AI · 4 min
Cross-Entropy Loss Drives Neural Probe Performance, Not Architecture
Pre-registered study shows cross-entropy training inflates logit norms 15x, accounting for most K-way energy probe gains over softmax baselines.
Apr 24, 2026 Read → - ai · arxiv/cs.AI · 8 min
GEM activation functions match ReLU speed with smoother gradients
Krause proposes rational activation functions with tunable smoothness that reduce optimization friction in deep networks while maintaining computational efficiency.
Apr 24, 2026 Read → - engineering · arxiv/cs.AI · 6 min
Vibration Gestures on Furniture via Efficient FPGA Neural Networks
Researchers compress neural networks for gesture recognition on low-power FPGAs, eliminating complex preprocessing and cutting energy use to under 1.2 mJ per inference.
Apr 22, 2026 Read → - engineering · arxiv/cs.LG · 4 min
Hybrid PINNs: Finite-Difference Regularization for Physics Solvers
Adding weak finite-difference gradient penalties to physics-informed neural networks improves boundary accuracy without replacing automatic-differentiation residuals.
Apr 17, 2026 Read →