Michael Chang

I am a Ph.D. student in Computer Science at U.C. Berkeley. I am a member of Berkeley AI Research.

This summer I was a research intern at Istituto Dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA) under the supervision of Professor Jürgen Schmidhuber.

Earlier this year, I graduated with a B.S. in Computer Science from MIT, where I researched in CSAIL and BCS with Professors Josh Tenenbaum and Antonio Torralba.

Previously I worked at Google, at the University of Michigan Ann Arbor with Professor Honglak Lee, at the MIT Media Lab with Professor Pattie Maes, and as Strategy Lead in the MIT Solar Electric Vehicle Team.

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[ News | Talks | Research | Readings | Heroes]

News
  • January 2018: "Relational Neural Expectation Maximization: Unsupervised Discovery of Objects and their Interactions" has been accepted to ICLR 2018.
  • December 2017: Our NIPS workshop paper on Relational Neural Expectation Maximization received the Outstanding Paper Award sponsored by Oculus.
  • February 2017: "A Compositional Object-Based Approach to Learning Physical Dynamics" has been accepted to ICLR 2017.
  • March 2016: "Understanding Visual Concepts with Continuation Learning" has been accepted to ICLR 2016 Workshop.
  • March 2015: Press Article - Finger-Mounted Reading Device for the Blind, with Roy Shilkrot and Marcelo Polanco.
Talks
Research

I am interested in the inductive biases and algorithmic constraints that guide learning agents to learn to develop their own languages for representing problems and modeling their world.

I have pursued this research vision from several perspectives: unsupervised learning of disentangled representations, neural architectures that capture regularities in environment dynamics, and bridging perception and symbolic reasoning.

Relational Neural Expectation Maximization: Unsupervised Discovery of Objects and their Interactions
Sjoerd van Steenkiste, Michael Chang, Klaus Greff, Jürgen Schmidhuber
Proceedings of the International Conference on Learning Representations (ICLR), 2018
project webpage / code

We present a novel method that learns to discover objects and model their physical interactions from raw visual images in a purely unsupervised fashion. It incorporates prior knowledge about the compositional nature of human perception to factor interactions between object-pairs and learn efficiently. On videos of bouncing balls we show the superior modeling capabilities of our method compared to other unsupervised neural approaches that do not incorporate such prior knowledge.

Relational Neural Expectation Maximization
Sjoerd van Steenkiste, Michael Chang, Klaus Greff, Jürgen Schmidhuber
NIPS workshop on Cognitively Informed Artificial Intelligence, 2017
Oral Presentation, Oculus Outstanding Paper Award

We propose a novel approach to common-sense physical reasoning that learns physical interactions between objects from raw visual images in a purely unsupervised fashion. Our method incorporates prior knowledge about the compositional nature of human perception, enabling it to discover objects, factor interactions between object-pairs to learn efficiently, and generalize to new environments without re-training.

A Compositional Object-Based Approach to Learning Physical Dynamics
Michael B. Chang, Tomer D. Ullman, Antonio Torralba, Joshua B. Tenenbaum
Proceedings of the International Conference on Learning Representations (ICLR), 2017
project webpage / code / poster / spotlight talk (NIPS Intuitive Physics Workshop)

The Neural Physics Engine (NPE) frames learning a simulator of intuitive physics as learning a compositional program over objects and interactions. This allows the NPE to naturally generalize across variable object count and different scene configurations.

Understanding Visual Concepts with Continuation Learning
William F. Whitney, Michael B. Chang, Tejas D. Kulkarni, Joshua B. Tenenbaum
International Conference on Learning Representations (ICLR) workshop, 2016
project webpage / code

This paper presents an unsupervised approach to learning factorized symbolic representations of high-level visual concepts by exploiting temporal continuity in the scene.

Readings

Here are some of my past and current readings that have changed the way I think.


Longer Works

The Society of Mind - Marvin Minsky

Three Kingdoms - Luo Guanzhong

The Beginning of Infinity - David Deutsch

The Little Prince - Antoine de Saint-Exupéry

Zhuangzi - Zhuangzi

The Structure of Scientific Revolutions - Thomas Kuhn

Hegemony or Survival - Noam Chomsky

Reinforcement Learning: An Introduction - Richard S. Sutton and Andrew G. Barto

Gödel, Escher, Bach: an Eternal Golden Braid - Douglas Hofstadter

Structure and Interpretation of Computer Programs - Harold Abelson and Gerald Sussman with Julie Sussman

The Feynman Lectures on Physics - Richard P. Feynman, Robert B. Leighton, Matthew Sands

Republic - Plato

Tao Te Ching - Laozi


Shorter Works

A Psalm of Life - Henry Wadsworth Longfellow

You and Your Research - Richard Hamming

Building Machines that Think and Learn Like People - Brendan M. Lake, Tomer D. Ullman, Joshua B. Tenenbaum, Samuel J. Gershman

Steps Toward Artificial Intelligence - Marvin Minsky

As We May Think - Vannevar Bush

The Philosophy of Composition - Edgar Allan Poe


Others' Reading Lists

Lucas Morales' reading list

MIT Probabilistic Computing Project's reading list

Jürgen Schmidhuber's recommended readings

Gerry Sussman's reading list

Marcus Hutter's reading list

Patrick Winston's reading list

Tom Griffith's reading list

Heroes

Here are some of my heroes that have shaped my worldview.

Master Cheng Yen

Happiest is the person whose heart is filled with love.

We cannot love when filled with suspicion; we cannot forgive when unwilling to believe; we cannot trust when filled with doubts.

Blessed are those who have the ability to love and be loved by others.

Clear conscience brings peace of mind; the greatest happiness comes from the pleasure of giving and helping others.

Having the ability to help others is a blessing.

To forgive others is, in fact, being kind to ourselves.

Being filial is not making our parents unduly worry about us.

Do whatever it takes to do what is right. Do whatever it takes to not do what is wrong.

Being angry is a form of torturing ourselves with the mistakes of others.

Only when we light up our heart, can we inspire others to do the same.

If our thoughts are upright and wholesome, we can always be at ease and evil cannot come near.

To a beautiful heart, everything appears beautiful.

Do not fear making mistakes in life, fear only not correcting them.

Bruce Lee

Knowledge will give you power, but character respect.

As you think, so you shall become.

Mistakes are always forgivable, if one has the courage to admit them.

If you love life, don't waste time, for time is what life is made up of.

The key to immortality is first living a life worth remembering.

Do not pray for an easy life, pray for the strength to endure a difficult one.

The self-sufficient stand alone - most people follow the crowd and imitate.

Notice that that the stiffest tree is easily cracked, while the bamboo or willow survives by bending with the wind.

Patience is not passive; on the contrary it is concentrated strength.

What is defeat? Nothing but education. Nothing but the first step to something better.

Success means doing something sincerely and wholeheartedly.

It is compassion rather than the principle of justice which can guard us against being unjust to our fellow man.


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