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Ai Infrastructure

[D] Building a demand forecasting system for multi-location retail with no POS integration, architecture feedback wanted

We’re building a lightweight demand forecasting engine on top of manually entered operational data. No POS integration, no external feeds...

Reddit - Machine Learning · 1 min ·
UMKC Announces New Master of Science in Artificial Intelligence
Ai Infrastructure

UMKC Announces New Master of Science in Artificial Intelligence

UMKC announces a new Master of Science in Artificial Intelligence program aimed at addressing workforce demand for AI expertise, set to l...

AI News - General · 4 min ·
Machine Learning

[D] Looking for definition of open-world ish learning problem

Hello! Recently I did a project where I initially had around 30 target classes. But at inference, the model had to be able to handle a lo...

Reddit - Machine Learning · 1 min ·

All Content

Llms

[D] Probabilistic Neuron Activation in Predictive Coding Algorithm using 1 Bit LLM Architecture

If we use Predictive Coding architecture we wouldn't need backpropogation anymore which would work well for a non deterministic system th...

Reddit - Machine Learning · 1 min ·
Llms

Google Gemini still has no native chat export in 2025. Here's how I solved it for my research workflow.

One thing that's always bothered me about Gemini: you can run a 30-minute Deep Research session, get an incredible research report with 4...

Reddit - Artificial Intelligence · 1 min ·
[2603.14831] Neural Networks as Local-to-Global Computations
Machine Learning

[2603.14831] Neural Networks as Local-to-Global Computations

Abstract page for arXiv paper 2603.14831: Neural Networks as Local-to-Global Computations

arXiv - Machine Learning · 4 min ·
[2602.07058] SPARE: Self-distillation for PARameter-Efficient Removal
Machine Learning

[2602.07058] SPARE: Self-distillation for PARameter-Efficient Removal

Abstract page for arXiv paper 2602.07058: SPARE: Self-distillation for PARameter-Efficient Removal

arXiv - Machine Learning · 4 min ·
[2507.00629] Generalization performance of narrow one-hidden layer networks in the teacher-student setting
Machine Learning

[2507.00629] Generalization performance of narrow one-hidden layer networks in the teacher-student setting

Abstract page for arXiv paper 2507.00629: Generalization performance of narrow one-hidden layer networks in the teacher-student setting

arXiv - Machine Learning · 4 min ·
[2506.20334] Recurrent neural network-based robust control systems with regional properties and application to MPC design
Machine Learning

[2506.20334] Recurrent neural network-based robust control systems with regional properties and application to MPC design

Abstract page for arXiv paper 2506.20334: Recurrent neural network-based robust control systems with regional properties and application ...

arXiv - Machine Learning · 4 min ·
[2505.20714] Wideband RF Radiance Field Modeling Using Frequency-embedded 3D Gaussian Splatting
Machine Learning

[2505.20714] Wideband RF Radiance Field Modeling Using Frequency-embedded 3D Gaussian Splatting

Abstract page for arXiv paper 2505.20714: Wideband RF Radiance Field Modeling Using Frequency-embedded 3D Gaussian Splatting

arXiv - Machine Learning · 4 min ·
[2405.17573] Hamiltonian Mechanics of Feature Learning: Bottleneck Structure in Leaky ResNets
Ai Infrastructure

[2405.17573] Hamiltonian Mechanics of Feature Learning: Bottleneck Structure in Leaky ResNets

Abstract page for arXiv paper 2405.17573: Hamiltonian Mechanics of Feature Learning: Bottleneck Structure in Leaky ResNets

arXiv - Machine Learning · 4 min ·
[2603.16661] Self-Aware Markov Models for Discrete Reasoning
Machine Learning

[2603.16661] Self-Aware Markov Models for Discrete Reasoning

Abstract page for arXiv paper 2603.16661: Self-Aware Markov Models for Discrete Reasoning

arXiv - Machine Learning · 4 min ·
[2603.13909] FedPBS: Proximal-Balanced Scaling Federated Learning Model for Robust Personalized Training for Non-IID Data
Machine Learning

[2603.13909] FedPBS: Proximal-Balanced Scaling Federated Learning Model for Robust Personalized Training for Non-IID Data

Abstract page for arXiv paper 2603.13909: FedPBS: Proximal-Balanced Scaling Federated Learning Model for Robust Personalized Training for...

arXiv - Machine Learning · 4 min ·
[2511.11743] Uncertainty Makes It Stable: Curiosity-Driven Quantized Mixture-of-Experts
Machine Learning

[2511.11743] Uncertainty Makes It Stable: Curiosity-Driven Quantized Mixture-of-Experts

Abstract page for arXiv paper 2511.11743: Uncertainty Makes It Stable: Curiosity-Driven Quantized Mixture-of-Experts

arXiv - Machine Learning · 4 min ·
[2511.06767] QUARK: Quantization-Enabled Circuit Sharing for Transformer Acceleration by Exploiting Common Patterns in Nonlinear Operations
Machine Learning

[2511.06767] QUARK: Quantization-Enabled Circuit Sharing for Transformer Acceleration by Exploiting Common Patterns in Nonlinear Operations

Abstract page for arXiv paper 2511.06767: QUARK: Quantization-Enabled Circuit Sharing for Transformer Acceleration by Exploiting Common P...

arXiv - Machine Learning · 4 min ·
[2511.04854] SigmaDock: Untwisting Molecular Docking With Fragment-Based SE(3) Diffusion
Generative Ai

[2511.04854] SigmaDock: Untwisting Molecular Docking With Fragment-Based SE(3) Diffusion

Abstract page for arXiv paper 2511.04854: SigmaDock: Untwisting Molecular Docking With Fragment-Based SE(3) Diffusion

arXiv - Machine Learning · 4 min ·
[2508.17381] DART: A Server-side Plug-in for Resource-efficient Robust Federated Learning
Machine Learning

[2508.17381] DART: A Server-side Plug-in for Resource-efficient Robust Federated Learning

Abstract page for arXiv paper 2508.17381: DART: A Server-side Plug-in for Resource-efficient Robust Federated Learning

arXiv - Machine Learning · 3 min ·
[2506.06303] Reward Is Enough: LLMs Are In-Context Reinforcement Learners
Llms

[2506.06303] Reward Is Enough: LLMs Are In-Context Reinforcement Learners

Abstract page for arXiv paper 2506.06303: Reward Is Enough: LLMs Are In-Context Reinforcement Learners

arXiv - Machine Learning · 4 min ·
[2505.16950] Bottlenecked Transformers: Periodic KV Cache Consolidation for Generalised Reasoning
Llms

[2505.16950] Bottlenecked Transformers: Periodic KV Cache Consolidation for Generalised Reasoning

Abstract page for arXiv paper 2505.16950: Bottlenecked Transformers: Periodic KV Cache Consolidation for Generalised Reasoning

arXiv - Machine Learning · 4 min ·
[2502.01521] Symmetry-Guided Memory Augmentation for Efficient Locomotion Learning
Machine Learning

[2502.01521] Symmetry-Guided Memory Augmentation for Efficient Locomotion Learning

Abstract page for arXiv paper 2502.01521: Symmetry-Guided Memory Augmentation for Efficient Locomotion Learning

arXiv - Machine Learning · 3 min ·
[2406.00300] Coded Computing for Resilient Distributed Computing: A Learning-Theoretic Framework
Ai Infrastructure

[2406.00300] Coded Computing for Resilient Distributed Computing: A Learning-Theoretic Framework

Abstract page for arXiv paper 2406.00300: Coded Computing for Resilient Distributed Computing: A Learning-Theoretic Framework

arXiv - Machine Learning · 4 min ·
[2603.24196] Quantum Neural Physics: Solving Partial Differential Equations on Quantum Simulators using Quantum Convolutional Neural Networks
Machine Learning

[2603.24196] Quantum Neural Physics: Solving Partial Differential Equations on Quantum Simulators using Quantum Convolutional Neural Networks

Abstract page for arXiv paper 2603.24196: Quantum Neural Physics: Solving Partial Differential Equations on Quantum Simulators using Quan...

arXiv - Machine Learning · 4 min ·
[2603.24041] Minimal Sufficient Representations for Self-interpretable Deep Neural Networks
Machine Learning

[2603.24041] Minimal Sufficient Representations for Self-interpretable Deep Neural Networks

Abstract page for arXiv paper 2603.24041: Minimal Sufficient Representations for Self-interpretable Deep Neural Networks

arXiv - Machine Learning · 3 min ·
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