https://www.cambridge.org/core/journals/mathematical-structures-in-computer-science/article/abs/deep-inference-and-expansion-trees-for-secondorder-multiplicative-linear-logic/812A36241CD7BBBB5E92C157A7767972
Deep inference and expansion trees for second-order multiplicative linear logic | Mathematical...
Deep inference and expansion trees for second-order multiplicative linear logic - Volume 29 Issue 8
deep inference
https://en.wikipedia.org/wiki/Deep_inference
Deep inference - Wikipedia
deep inferencewikipedia
https://github.com/zkonduit/ezkl
GitHub - zkonduit/ezkl: ezkl is an engine for doing inference for deep learning models and other...
ezkl is an engine for doing inference for deep learning models and other computational graphs in a zk-snark (ZKML). Use it from Python, Javascript, or the...
https://deepai.org/publication/xonn-xnor-based-oblivious-deep-neural-network-inference
XONN: XNOR-based Oblivious Deep Neural Network Inference | DeepAI
Feb 19, 2019 - 02/19/19 - Advancements in deep learning enable cloud servers to provide inference-as-a-service for clients. In this scenario, clients send t...
deep neural networkxnorbasedobliviousinference
https://www.amazon.science/publications/ring-net-road-inference-from-gps-trajectories-using-a-deep-segmentation-network
RING-Net: Road inference from GPS trajectories using a deep segmentation network - Amazon Science
Accurate and rich representation of roads in a map is critical for safe and efficient navigation experience. Often, open source road data is incomplete and...
https://www.aanda.org/articles/aa/ref/2025/06/aa53786-25/aa53786-25.html
Deep learning inference with the Event Horizon Telescope - III. ZINGULARITY results from the 2017...
deep learning inferencethe event horizon
https://github.com/fabi92/eccv18-rgb_pose_refinement
GitHub - fabi92/eccv18-rgb_pose_refinement: Inference code and trained networks for Deep...
Inference code and trained networks for Deep Model-Based 6D Pose Refinement in RGB - fabi92/eccv18-rgb_pose_refinement
https://arxiv.org/abs/2101.01163
[2101.01163] SmartDeal: Re-Modeling Deep Network Weights for Efficient Inference and Training
Abstract page for arXiv paper 2101.01163: SmartDeal: Re-Modeling Deep Network Weights for Efficient Inference and Training
https://arxiv.org/abs/2105.02866
[2105.02866] Membership Inference Attacks on Deep Regression Models for Neuroimaging
Abstract page for arXiv paper 2105.02866: Membership Inference Attacks on Deep Regression Models for Neuroimaging
regression models2105membershipinferenceattacks
https://openreview.net/forum?id=n0arS0DDot
BLAST: Block-Level Adaptive Structured Matrices for Efficient Deep Neural Network Inference |...
Large-scale foundation models have demonstrated exceptional performance in language and vision tasks. However, the numerous dense matrix-vector operations...
deep neural networkblock level
https://openreview.net/forum?id=ZlbywpCCXJ&referrer=%5Bthe%20profile%20of%20Chenghao%20Huang%5D(%2Fprofile%3Fid%3D~Chenghao_Huang2)
Inference-Based Deep Reinforcement Learning for Physics-Based Character Control | OpenReview
Character motion synthesis and control has shown great significance in the field of character animation. Synthesizing more human-like behaviors and motion...
deep reinforcement learninginferencebasedphysicscharacter
https://arxiv.org/abs/2301.12378
[2301.12378] Towards Inference Efficient Deep Ensemble Learning
Abstract page for arXiv paper 2301.12378: Towards Inference Efficient Deep Ensemble Learning
2301towardsinferenceefficientdeep
https://openreview.net/forum?id=dqgdBy4Uv5
Cheap and Deterministic Inference for Deep State-Space Models of Interacting Dynamical Systems |...
Graph neural networks are often used to model interacting dynamical systems since they gracefully scale to systems with a varying and high number of agents....
state space models
https://arxiv.org/abs/1907.07504
[1907.07504] Subspace Inference for Bayesian Deep Learning
Abstract page for arXiv paper 1907.07504: Subspace Inference for Bayesian Deep Learning
1907subspaceinferencebayesiandeep
https://www.tomshardware.com/news/intel-xeon-cpu-fpga-ai,33036.html
Intel Launches New Xeon CPU, Announces Deep Learning Inference Accelerator | Tom's Hardware
Nov 16, 2016 - Intel announced a new CPU at SC16 and also introduced its new FPGA-powered Deep Learning Inference Accelerator.
deep learning inference
https://deepai.org/publication/compute-and-energy-consumption-trends-in-deep-learning-inference
Compute and Energy Consumption Trends in Deep Learning Inference | DeepAI
Sep 12, 2021 - 09/12/21 - The progress of some AI paradigms such as deep learning is said to be linked to an exponential growth in the number of parameters....
deep learning inferenceenergy consumptioncomputetrendsdeepai
https://openreview.net/forum?id=8lL_y9n-CV
Membership Inference Attacks on Deep Regression Models for Neuroimaging | OpenReview
We show realistic membership inference attacks on deep neural networks learned via either distributed or centralized training to predict brain age from MRI...
regression modelsmembershipinferenceattacksdeep
https://pmc.ncbi.nlm.nih.gov/articles/PMC10951644/
scGREAT: Transformer-based deep-language model for gene regulatory network inference from...
Gene regulatory networks (GRNs) involve complex and multi-layer regulatory interactions between regulators and their target genes. Precise knowledge of GRNs is...
gene regulatory networklanguage model
https://elifesciences.org/articles/80942v1
ProteInfer, deep neural networks for protein functional inference | eLife
deep neural networksproteinfunctionalinferenceelife