Search Results for author: Manoj Kumar

Found 14 papers, 7 papers with code

On the surprising tradeoff between ImageNet accuracy and perceptual similarity

no code implementations9 Mar 2022 Manoj Kumar, Neil Houlsby, Nal Kalchbrenner, Ekin D. Cubuk

Perceptual distances between images, as measured in the space of pre-trained deep features, have outperformed prior low-level, pixel-based metrics on assessing image similarity.

IISERB Brains at SemEval 2022 Task 6: A Deep-learning Framework to Identify Intended Sarcasm in English

1 code implementation4 Mar 2022 Tanuj Singh Shekhawat, Manoj Kumar, Udaybhan Rathore, Aditya Joshi, Jasabanta Patro

This paper describes the system architectures and the models submitted by our team "IISERBBrains" to SemEval 2022 Task 6 competition.

Skillful Twelve Hour Precipitation Forecasts using Large Context Neural Networks

1 code implementation14 Nov 2021 Lasse Espeholt, Shreya Agrawal, Casper Sønderby, Manoj Kumar, Jonathan Heek, Carla Bromberg, Cenk Gazen, Jason Hickey, Aaron Bell, Nal Kalchbrenner

An emerging class of weather models based on neural networks represents a paradigm shift in weather forecasting: the models learn the required transformations from data instead of relying on hand-coded physics and are computationally efficient.

Weather Forecasting

Coexistence of coarsening and mean field relaxation in the long-range Ising chain

no code implementations16 Feb 2021 Federico Corberi, Alessandro Iannone, Manoj Kumar, Eugenio Lippiello, Paolo Politi

We study the kinetics after a low temperature quench of the one-dimensional Ising model with long range interactions between spins at distance $r$ decaying as $r^{-\alpha}$.

Statistical Mechanics

Colorization Transformer

2 code implementations ICLR 2021 Manoj Kumar, Dirk Weissenborn, Nal Kalchbrenner

We present the Colorization Transformer, a novel approach for diverse high fidelity image colorization based on self-attention.


ProtoDA: Efficient Transfer Learning for Few-Shot Intent Classification

no code implementations28 Jan 2021 Manoj Kumar, Varun Kumar, Hadrien Glaude, Cyprien delichy, Aman Alok, Rahul Gupta

We make use of a conditional generator for data augmentation that is trained directly using the meta-learning objective and simultaneously with prototypical networks, hence ensuring that data augmentation is customized to the task.

Classification Data Augmentation +7

Necessary and Sufficient Condition for Satisfiability of a Boolean Formula in CNF and its Implications on P versus NP problem

no code implementations13 Jan 2021 Manoj Kumar

Which leads to the necessary and sufficient condition for satisfiability of a boolean formula, in CNF.

Computational Complexity

Designing Neural Speaker Embeddings with Meta Learning

1 code implementation31 Jul 2020 Manoj Kumar, Tae Jin-Park, Somer Bishop, Shrikanth Narayanan

Our experiments illustrate the applicability of meta-learning as a generalized learning paradigm for training deep neural speaker embeddings.

Audio and Speech Processing Sound

Auto-Tuning Spectral Clustering for Speaker Diarization Using Normalized Maximum Eigengap

2 code implementations5 Mar 2020 Tae Jin Park, Kyu J. Han, Manoj Kumar, Shrikanth Narayanan

In this study, we propose a new spectral clustering framework that can auto-tune the parameters of the clustering algorithm in the context of speaker diarization.

Speaker Diarization

Learning Domain Invariant Representations for Child-Adult Classification from Speech

no code implementations25 Oct 2019 Rimita Lahiri, Manoj Kumar, Somer Bishop, Shrikanth Narayanan

Diagnostic procedures for ASD (autism spectrum disorder) involve semi-naturalistic interactions between the child and a clinician.

General Classification

VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation

1 code implementation ICLR 2020 Manoj Kumar, Mohammad Babaeizadeh, Dumitru Erhan, Chelsea Finn, Sergey Levine, Laurent Dinh, Durk Kingma

Generative models that can model and predict sequences of future events can, in principle, learn to capture complex real-world phenomena, such as physical interactions.

Frame Predict Future Video Frames +1

Parallel Architecture and Hyperparameter Search via Successive Halving and Classification

1 code implementation25 May 2018 Manoj Kumar, George E. Dahl, Vijay Vasudevan, Mohammad Norouzi

We present a simple and powerful algorithm for parallel black box optimization called Successive Halving and Classification (SHAC).

Classification General Classification

Enabling Massive Deep Neural Networks with the GraphBLAS

no code implementations9 Aug 2017 Jeremy Kepner, Manoj Kumar, José Moreira, Pratap Pattnaik, Mauricio Serrano, Henry Tufo

The performance of the GraphBLAS implementation is measured relative to a standard dense linear algebra library implementation.

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