activity
20192026
most citedAccelerating Sparse Deep Neural Networks

14 citations · 31 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CL2026

Nemotron 3 Ultra: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning

NVIDIA, :, Aaron Blakeman +572

We introduce Nemotron 3 Ultra, a 550 billion total and 55 billion active parameter Mixture-of-Experts Hybrid Mamba-Attention language model. We pre-trained Nemotron 3 Ultra on 20 t…

cs.LG2026

Nemotron 3 Super: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning

NVIDIA, :, Aakshita Chandiramani +544

We describe the pre-training, post-training, and quantization of Nemotron 3 Super, a 120 billion (active 12 billion) parameter hybrid Mamba-Attention Mixture-of-Experts model. Nemo…

cs.CL2025★ 1 cited

NVIDIA Nemotron 3: Efficient and Open Intelligence

NVIDIA, :, Aaron Blakeman +356

We introduce the Nemotron 3 family of models - Nano, Super, and Ultra. These models deliver strong agentic, reasoning, and conversational capabilities. The Nemotron 3 family uses a…

cs.CL2025

Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning

NVIDIA, :, Aaron Blakeman +311

We present Nemotron 3 Nano 30B-A3B, a Mixture-of-Experts hybrid Mamba-Transformer language model. Nemotron 3 Nano was pretrained on 25 trillion text tokens, including more than 3 t…

cs.CL2025

Pretraining Large Language Models with NVFP4

NVIDIA, Felix Abecassis, Anjulie Agrusa +87

Large Language Models (LLMs) today are powerful problem solvers across many domains, and they continue to get stronger as they scale in model size, training set size, and training…

cond-mat.stat-mech2022

Ising models of deep neural networks

Dusan Stosic, Darko Stosic, Borko Stosic

This work maps deep neural networks to classical Ising spin models, allowing them to be described using statistical thermodynamics. The density of states shows that structures emer…

cond-mat.stat-mech2022

Generalized Weighted Permutation Entropy

Darko Stosic, Dusan Stosic, Tatijana Stosic +1

A novel heuristic approach is proposed here for time series data analysis, dubbed Generalized weighted permutation entropy, which amalgamates and generalizes beyond their original…

q-fin.ST2021★ 9 cited

A new look at calendar anomalies: Multifractality and day of the week effect

Darko Stosic, Dusan Stosic, Irena Vodenska +2

Stock markets can become inefficient due to calendar anomalies known as day-of-the-week effect. Calendar anomalies are well-known in financial literature, but the phenomena remain…

cs.LG2021

Distance Metric Learning through Minimization of the Free Energy

Dusan Stosic, Darko Stosic, Teresa B. Ludermir +1

Distance metric learning has attracted a lot of interest for solving machine learning and pattern recognition problems over the last decades. In this work we present a simple appro…

cs.LG2021★ 1 cited

Search Spaces for Neural Model Training

Darko Stosic, Dusan Stosic

While larger neural models are pushing the boundaries of what deep learning can do, often more weights are needed to train models rather than to run inference for tasks. This paper…

cs.LG2021★ 14 cited

Accelerating Sparse Deep Neural Networks

Asit Mishra, Jorge Albericio Latorre, Jeff Pool +5

As neural network model sizes have dramatically increased, so has the interest in various techniques to reduce their parameter counts and accelerate their execution. An active area…

q-fin.ST2019★ 6 cited

Nonextensive triplets in stock market indices

Dusan Stosic, Darko Stosic, Tatijana Stosic

Stock market indices are one of the most investigated complex systems in econophysics. Here we extend the existing literature on stock markets in connection with nonextensive stati…