b'Mark Sandler'

research

∙ 08/12/2022

DDX7: Differentiable FM Synthesis of Musical Instrument Sounds

FM Synthesis is a well-known algorithm used to generate complex timbre f...

Franco Caspe, et al. ∙

research

∙ 07/15/2022

Anomalous behaviour in loss-gradient based interpretability methods

Loss-gradients are used to interpret the decision making process of deep...

Vinod Subramanian, et al. ∙

research

∙ 04/10/2022

Deep Conditional Representation Learning for Drum Sample Retrieval by Vocalisation

Imitating musical instruments with the human voice is an efficient way o...

Alejandro Delgado, et al. ∙

research

∙ 04/10/2022

Deep Embeddings for Robust User-Based Amateur Vocal Percussion Classification

Vocal Percussion Transcription (VPT) is concerned with the automatic det...

Alejandro Delgado, et al. ∙

research

∙ 03/29/2022

Fine-tuning Image Transformers using Learnable Memory

In this paper we propose augmenting Vision Transformer models with learn...

Mark Sandler, et al. ∙

research

∙ 01/11/2022

HyperTransformer: Model Generation for Supervised and Semi-Supervised Few-Shot Learning

In this work we propose a HyperTransformer, a transformer-based model fo...

Andrey Zhmoginov, et al. ∙

research

∙ 10/18/2021

Learning Models for Query by Vocal Percussion: A Comparative Study

The imitation of percussive sounds via the human voice is a natural and ...

Alejandro Delgado, et al. ∙

research

∙ 07/23/2021

Compositional Models: Multi-Task Learning and Knowledge Transfer with Modular Networks

Conditional computation and modular networks have been recently proposed...

Andrey Zhmoginov, et al. ∙

research

∙ 04/10/2021

Meta-Learning Bidirectional Update Rules

In this paper, we introduce a new type of generalized neural network whe...

Mark Sandler, et al. ∙

research

∙ 03/24/2021

Transfer Learning for Piano Sustain-Pedal Detection

Detecting piano pedalling techniques in polyphonic music remains a chall...

Beici Liang, et al. ∙

research

∙ 01/04/2021

SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection

Deep learning based object detectors are commonly deployed on mobile dev...

Keren Ye, et al. ∙

research

∙ 12/10/2020

Large-Scale Generative Data-Free Distillation

Knowledge distillation is one of the most popular and effective techniqu...

Liangchen Luo, et al. ∙

research

∙ 08/11/2020

Image segmentation via Cellular Automata

In this paper, we propose a new approach for building cellular automata ...

Mark Sandler, et al. ∙

research

∙ 11/25/2019

Structured Multi-Hashing for Model Compression

Despite the success of deep neural networks (DNNs), state-of-the-art mod...

Elad Eban, et al. ∙

research

∙ 09/07/2019

Non-discriminative data or weak model? On the relative importance of data and model resolution

We explore the question of how the resolution of the input image ("input...

Mark Sandler, et al. ∙

research

∙ 07/22/2019

Information-Bottleneck Approach to Salient Region Discovery

We propose a new method for learning image attention masks in a semi-sup...

Andrey Zhmoginov, et al. ∙

research

∙ 07/04/2019

Adversarial Attacks in Sound Event Classification

Adversarial attacks refer to a set of methods that perturb the input to ...

Vinod Subramanian, et al. ∙

research

∙ 05/08/2019

Efficient On-line Computation of Visibility Graphs

A visibility algorithm maps time series into complex networks following ...

Benito García, et al. ∙

research

∙ 05/06/2019

Searching for MobileNetV3

We present the next generation of MobileNets based on a combination of c...

Andrew Howard, et al. ∙

research

∙ 03/05/2019

Visibility graphs for robust harmonic similarity measures between audio spectra

Graph theory is emerging as a new source of tools for time series analys...

Benito García, et al. ∙

research

∙ 10/25/2018

K For The Price Of 1: Parameter Efficient Multi-task And Transfer Learning

We introduce a novel method that enables parameter-efficient transfer an...

Pramod Kaushik Mudrakarta, et al. ∙

research

∙ 04/06/2018

Does k Matter? k-NN Hubness Analysis for Kernel Additive Modelling Vocal Separation

Kernel Additive Modelling (KAM) is a framework for source separation aim...

Benito García, et al. ∙

research

∙ 02/14/2018

Similarity measures for vocal-based drum sample retrieval using deep convolutional auto-encoders

The expressive nature of the voice provides a powerful medium for commun...

Adib Mehrabi, et al. ∙

research

∙ 01/13/2018

Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segmentation

In this paper we describe a new mobile architecture, MobileNetV2, that i...

Mark Sandler, et al. ∙

research

∙ 01/13/2018

Inverted Residuals and Linear Bottlenecks: Mobile Networks forClassification, Detection and Segmentation

In this paper we describe a new mobile architecture, MobileNetV2, that i...

Mark Sandler, et al. ∙

research

∙ 12/08/2017

CycleGAN: a Master of Steganography

CycleGAN is one of the latest successful approaches to learn a correspon...

Casey Chu, et al. ∙

research

∙ 09/13/2017

A Tutorial on Deep Learning for Music Information Retrieval

Following their success in Computer Vision and other areas, deep learnin...

Keunwoo Choi, et al. ∙

research

∙ 09/06/2017

A Comparison on Audio Signal Preprocessing Methods for Deep Neural Networks on Music Tagging

Deep neural networks (DNN) have been successfully applied for music clas...

Keunwoo Choi, et al. ∙

research

∙ 06/07/2017

The Effects of Noisy Labels on Deep Convolutional Neural Networks for Music Tagging

Deep neural networks (DNN) have been successfully applied to music class...

Keunwoo Choi, et al. ∙

research

∙ 03/27/2017

Transfer learning for music classification and regression tasks

In this paper, we present a transfer learning approach for music classif...

Keunwoo Choi, et al. ∙

research

∙ 02/21/2017

The Power of Sparsity in Convolutional Neural Networks

Deep convolutional networks are well-known for their high computational ...

Soravit Changpinyo, et al. ∙

research

∙ 09/14/2016

Convolutional Recurrent Neural Networks for Music Classification

We introduce a convolutional recurrent neural network (CRNN) for music t...

Keunwoo Choi, et al. ∙

research

∙ 08/17/2016

Towards Music Captioning: Generating Music Playlist Descriptions

Descriptions are often provided along with recommendations to help users...

Keunwoo Choi, et al. ∙

research

∙ 07/08/2016

Explaining Deep Convolutional Neural Networks on Music Classification

Deep convolutional neural networks (CNNs) have been actively adopted in ...

Keunwoo Choi, et al. ∙

research

∙ 06/14/2016

Inverting face embeddings with convolutional neural networks

Deep neural networks have dramatically advanced the state of the art for...

Andrey Zhmoginov, et al. ∙

research

∙ 06/07/2016

Towards Playlist Generation Algorithms Using RNNs Trained on Within-Track Transitions

We introduce a novel playlist generation algorithm that focuses on the q...

Keunwoo Choi, et al. ∙

Mark Sandler

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