9.7k citations · 10.7k across the 9 of their papers we have counts for
10 papers
On Thread Convergence
Vinod Grover, Manjunath Kudlur
We introduce a notion of convergence for the nodes and edges of a control-flow graph that captures whether a barrier placed at that location is guaranteed to synchronize all thread…
Moonshine v2: Ergodic Streaming Encoder ASR for Latency-Critical Speech Applications
Manjunath Kudlur, Evan King, James Wang +1
Latency-critical speech applications (e.g., live transcription, voice commands, and real-time translation) demand low time-to-first-token (TTFT) and high transcription accuracy, pa…
Flavors of Moonshine: Tiny Specialized ASR Models for Edge Devices
Evan King, Adam Sabra, Manjunath Kudlur +2
We present the Flavors of Moonshine, a suite of tiny automatic speech recognition (ASR) models specialized for a range of underrepresented languages. Prevailing wisdom suggests tha…
Moonshine: Speech Recognition for Live Transcription and Voice Commands
Nat Jeffries, Evan King, Manjunath Kudlur +3
This paper introduces Moonshine, a family of speech recognition models optimized for live transcription and voice command processing. Moonshine is based on an encoder-decoder trans…
Wake Vision: A Tailored Dataset and Benchmark Suite for TinyML Computer Vision Applications
Colby Banbury, Emil Njor, Andrea Mattia Garavagno +7
Tiny machine learning (TinyML) co-locates models with sensors on microcontrollers, where small models (which are disproportionately sensitive to label noise) and bespoke binary tas…
Dynamic Control Flow in Large-Scale Machine Learning
Yuan Yu, Martín Abadi, Paul Barham +12
Many recent machine learning models rely on fine-grained dynamic control flow for training and inference. In particular, models based on recurrent neural networks and on reinforcem…
Exploring the structure of a real-time, arbitrary neural artistic stylization network
Golnaz Ghiasi, Honglak Lee, Manjunath Kudlur +2
In this paper, we present a method which combines the flexibility of the neural algorithm of artistic style with the speed of fast style transfer networks to allow real-time styliz…
A Learned Representation For Artistic Style
Vincent Dumoulin, Jonathon Shlens, Manjunath Kudlur
The diversity of painting styles represents a rich visual vocabulary for the construction of an image. The degree to which one may learn and parsimoniously capture this visual voca…
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Martín Abadi, Ashish Agarwal, Paul Barham +37
TensorFlow is an interface for expressing machine learning algorithms, and an implementation for executing such algorithms. A computation expressed using TensorFlow can be executed…
Order Matters: Sequence to sequence for sets
Oriol Vinyals, Samy Bengio, Manjunath Kudlur
Sequences have become first class citizens in supervised learning thanks to the resurgence of recurrent neural networks. Many complex tasks that require mapping from or to a sequen…