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09/14/2023
Beta Diffusion
We introduce beta diffusion, a novel generative modeling method that int...
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05/28/2023
Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling
Learning to denoise has emerged as a prominent paradigm to design state-...
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05/17/2023
ACRoBat: Optimizing Auto-batching of Dynamic Deep Learning at Compile Time
Dynamic control flow is an important technique often used to design expr...
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02/20/2023
Bayesian subtyping for multi-state brain functional connectome with application on adolescent brain cognition
Converging evidence indicates that the heterogeneity of cognitive profil...
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02/08/2023
ED-Batch: Efficient Automatic Batching of Dynamic Neural Networks via Learned Finite State Machines
Batching has a fundamental influence on the efficiency of deep neural ne...
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08/25/2022
SONAR: Joint Architecture and System Optimization Search
There is a growing need to deploy machine learning for different tasks o...
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07/11/2022
SparseTIR: Composable Abstractions for Sparse Compilation in Deep Learning
Sparse tensors are rapidly becoming critical components of modern deep l...
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07/09/2022
TensorIR: An Abstraction for Automatic Tensorized Program Optimization
Deploying deep learning models on various devices has become an importan...
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05/26/2022
Tensor Program Optimization with Probabilistic Programs
Automatic optimization for tensor programs becomes increasingly importan...
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01/27/2022
Bayesian network mediation analysis with application to brain functional connectome
Brain functional connectome, the collection of interconnected neural cir...
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11/01/2021
Collage: Automated Integration of Deep Learning Backends
Strong demands for efficient deployment of Deep Learning (DL) applicatio...
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10/19/2021
The CoRa Tensor Compiler: Compilation for Ragged Tensors with Minimal Padding
There is often variation in the shape and size of input data used for de...
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08/15/2021
Deep Adversarially-Enhanced k-Nearest Neighbors
Recent works have theoretically and empirically shown that deep neural n...
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06/27/2021
ASK: Adversarial Soft k-Nearest Neighbor Attack and Defense
K-Nearest Neighbor (kNN)-based deep learning methods have been applied t...
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06/27/2021
Immuno-mimetic Deep Neural Networks (Immuno-Net)
Biomimetics has played a key role in the evolution of artificial neural ...
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03/27/2021
Automated Backend-Aware Post-Training Quantization
Quantization is a key technique to reduce the resource requirement and i...
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12/18/2020
RAILS: A Robust Adversarial Immune-inspired Learning System
Adversarial attacks against deep neural networks are continuously evolvi...
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11/02/2020
Cortex: A Compiler for Recursive Deep Learning Models
Optimizing deep learning models is generally performed in two steps: (i)...
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06/17/2020
Dynamic Tensor Rematerialization
Checkpointing enables training deep learning models under restricted mem...
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04/17/2019
Relay: A High-Level Compiler for Deep Learning
Frameworks for writing, compiling, and optimizing deep learning (DL) mod...
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04/17/2019
Relay: A High-Level IR for Deep Learning
Frameworks for writing, compiling, and optimizing deep learning (DL) mod...
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12/05/2018
ADARES: Adaptive Resource Management for Virtual Machines
Virtual execution environments allow for consolidation of multiple appli...
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10/25/2018
Automating Generation of Low Precision Deep Learning Operators
State of the art deep learning models have made steady progress in the f...
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09/26/2018
Relay: A New IR for Machine Learning Frameworks
Machine learning powers diverse services in industry including search, t...
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07/11/2018
VTA: An Open Hardware-Software Stack for Deep Learning
Hardware acceleration is an enabler for ubiquitous and efficient deep le...
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05/21/2018
Learning to Optimize Tensor Programs
We introduce a learning-based framework to optimize tensor programs for ...
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02/12/2018
TVM: An Automated End-to-End Optimizing Compiler for Deep Learning
There is an increasing need to bring machine learning to a wide diversit...
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02/12/2018
TVM: End-to-End Optimization Stack for Deep Learning
Scalable frameworks, such as TensorFlow, MXNet, Caffe, and PyTorch drive...
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12/03/2015
MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems
MXNet is a multi-language machine learning (ML) library to ease the deve...
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11/18/2015
Net2Net: Accelerating Learning via Knowledge Transfer
We introduce techniques for rapidly transferring the information stored ...
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06/15/2015
A Complete Recipe for Stochastic Gradient MCMC
Many recent Markov chain Monte Carlo (MCMC) samplers leverage continuous...
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05/05/2015
Empirical Evaluation of Rectified Activations in Convolutional Network
In this paper we investigate the performance of different types of recti...
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10/22/2014
A Parallel and Efficient Algorithm for Learning to Match
Many tasks in data mining and related fields can be formalized as matchi...
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02/17/2014
Stochastic Gradient Hamiltonian Monte Carlo
Hamiltonian Monte Carlo (HMC) sampling methods provide a mechanism for d...
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09/11/2011
