Proposals
Anthill Inside 2018

Anthill Inside 2018

On the current state of academic research, practice and development regarding Deep Learning and Artificial Intelligence.

Anthill Inside

India’s community of deep learning and artificial intelligence practitioners.

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2018

NIMHANS Convention Centre, Bengaluru

Call for proposals

All proposals

Confirmed sessions

Birds Of Feather (BOF) session: AI - ethics and privacy

Suchana Seth (@suchana)

  • 0 comments
  • Fri, 13 Jul

Birds Of Feather (BOF) session: AI and Product

Vijay Gabale (@vijaygabale)

  • 0 comments
  • Fri, 13 Jul

Birds Of Feather (BOF) session: Hubs and spokes of AI

Anuj Gupta (@anuj-gupta)

  • 0 comments
  • Fri, 13 Jul

Deep Learning in the Browser: Explorable Explanations, Model Inference & Rapid Prototyping

Amit Kapoor (@amitkaps)

  • 0 comments
  • Thu, 28 Jun

Building and driving adoption for a robust semantic search system

Hrishikesh Ganu (@hrishikeshvganu)

  • 0 comments
  • Tue, 12 Jun

Neural-network Field Aware Factorisation Machines for Online-behaviour Prediction

Gunjan Sharma (@gunjan-sharma)

  • 1 comments
  • Fri, 8 Jun

Building Knowledgeable Machines

Hari C M (@haricm) (proposing)

  • 0 comments
  • Wed, 6 Jun

Product Size Recommendation for Fashion E-commerce

lavanya TS (@lavanyats)

  • 0 comments
  • Mon, 14 May

Sarcasm Detection : Achilles Heel of sentiment analysis

Anuj Gupta (@anuj-gupta)

  • 0 comments
  • Tue, 8 May

Uncertainty in Deep Learning

Madhu Gopinathan (@mg123)

  • 0 comments
  • Mon, 7 May

The Sentimental Computer- the Art and Science of Making Computers Understand Sentiment and Emotion

Hari C M (@haricm) (proposing)

  • 2 comments
  • Wed, 2 May

Attention Mechanisms and Machine Reasoning

Ashwin (@srisriashwin)

  • 0 comments
  • Tue, 1 May

Going beyond what and asking why: Explainability in Machine/Deep Learning

Vineeth N Balasubramanian (@nbvineeth)

  • 0 comments
  • Mon, 23 Apr

The evolution in AI thinking and products of the next decade

Shailesh Kumar (@shkumar)

  • 2 comments
  • Tue, 17 Apr

Looking beyond LSTMs: Alternatives to Time Series Modelling using Neural Nets

Aditya Patel (@pataditya)

  • 0 comments
  • Sun, 15 Apr

Learning Real-time Object Detection In The Absence of Large-scale Datasets

Vijay Gabale (@vijaygabale)

  • 0 comments
  • Sat, 14 Apr

What you cannot do with Machine Learning

Harsh Gupta (@hargup13)

  • 1 comments
  • Sat, 31 Mar

Unconfirmed proposals

Combining Neural Networks and Regression Tree for Dynamic Pricing in Mobile Advertising

Wei Li (@weili)

  • 0 comments
  • Fri, 8 Jun

A very gentle introduction to deep reinforcement learning and applications

Hari C M (@haricm) (proposing)

  • 0 comments
  • Wed, 6 Jun

Make your own DL framework

Nithish Divakar (@nithishdivakar)

  • 7 comments
  • Mon, 14 May

Advances in Deep Learning : Lessons from the field

Akhilesh Singh (@meetdestiny)

  • 0 comments
  • Wed, 9 May

Introduction to Game Training using Deep RL

Jaley Dholakiya (@jaleydholakiya)

  • 1 comments
  • Mon, 7 May

Deep Learning Howlers: Downside of Learning only Statistical Regularities

Vijay Srinivas Agneeswaran, Ph.D (@vijayagneeswaran)

  • 3 comments
  • Thu, 3 May

The Catalog as a Catalyst - Bringing benefits of Big Data to MSMEs

Kalpit Desai (@kalpitdesai)

  • 2 comments
  • Thu, 26 Apr

How organizations can leverage 'Large Scale Graph Based Analytics’ to derive value from their data.

Upendra Singh (@upendrasingh)

  • 0 comments
  • Thu, 26 Apr

Know Your Diabetes Risk - Preventive Health through Risk Prediction and Knowledge Base

Krishna Bhavsar (@krishnabhavsar)

  • 4 comments
  • Tue, 17 Apr

Deep Learning - An example implementation

Krishna Bhavsar (@krishnabhavsar)

  • 6 comments
  • Tue, 17 Apr

Building IOT Data pipelines using Prediction IO

Puneeth N (@puneethnarayana)

  • 1 comments
  • Mon, 16 Apr

Machine Learning and Statistical Methods for Time Series Analysis

Aravind Putrevu (@aravindputrevu)

  • 1 comments
  • Mon, 16 Apr

Explaining Human Cognition through Deep Learning

Amar Lalwani (@amar1707)

  • 2 comments
  • Sun, 15 Apr

AI at the Edge: A Software Perspective

Saumya Suneja (@saumyas)

  • 2 comments
  • Sun, 15 Apr

Anomaly detection with Variational Autoencoders

Aditya Prasad Narisetty (@adityaprasadn)

  • 1 comments
  • Sat, 14 Apr

Building a next generation Speech & NLU Engine: In pursuit of a Multi-modal experience for Bixby

Vikram Vij (@vikramvij)

  • 0 comments
  • Fri, 13 Apr

Adversarial Attacks on Deep Learning

Gaurav Goswami (@gauravgoswami)

  • 2 comments
  • Thu, 12 Apr

How organizations can leverage 'Large Scale Graph Based Analytics’ to derive value from their data.

Upendra Singh (@upendrasingh)

  • 1 comments
  • Thu, 12 Apr

The Catalog as a Catalyst - Bringing benefits of Big Data to MSMEs

Kalpit Desai (@kalpitdesai)

  • 2 comments
  • Thu, 12 Apr

Applying Alexa’s Natural Language To Your Challenges

Sohan Maheshwar (@sohanm)

  • 0 comments
  • Tue, 10 Apr

A novel Interactive Framework for semi-automated labeling when ground truth resides in free text

Tapan Shah (@tapan-shah)

  • 2 comments
  • Sat, 31 Mar

A Hitchhiker's Guide to Modern Object Detection: A deep learning journey since 2012

Karanbir Chahal (@karanchahal)

  • 4 comments
  • Fri, 30 Mar

Deep Learning with High School Math (or Less)

Aakash N S (@aakashns)

  • 1 comments
  • Wed, 28 Mar

BigDL: Integrating Deep Learning with Apache Spark

Mukesh G (@mkgbv)

  • 1 comments
  • Wed, 21 Mar

Industrial Vision & Deep Learning for Manufacturing Quality Inspection

Dr. Chiranjiv Roy (@drroy)

  • 9 comments
  • Tue, 24 Oct