Michael Chang

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

Prior to coming to Berkeley, I spent time at Istituto Dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA) under the supervision of Professor Jürgen Schmidhuber.

I graduated in 2017 with a B.S. in Computer Science from MIT, where I researched in CSAIL and BCS under the supervision of 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
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

Holes - Louis Sachar

Harry Potter - J. K. Rowling

The Society of Mind - Marvin Minsky

三國演義 Romance of the Three Kingdoms - 羅貫中 Luo Guanzhong

The Beginning of Infinity - David Deutsch

The Little Prince - Antoine de Saint-Exupéry

莊子 Zhuangzi - 莊子 Zhuangzi

The Structure of Scientific Revolutions - Thomas Kuhn

Hegemony or Survival - Noam Chomsky

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

道德經 Tao Te Ching - 老子 Laozi

Discussions on Youth - Diasaku Ikeda


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

The Differences Between Tinkering and Research - Julian Togelius


References

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


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 Griffiths' reading list

Scott Aaronson's reading list


Blogs

Scott Aaronson's blog

Heroes

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

證嚴法師 Master Cheng Yen

充滿愛心的人最幸福。
Happiest is the person whose heart is filled with love.

對人有疑心,就無法愛人;對人有疑念,就無法原諒人;對人有疑感,就無法相信人。
We cannot love when filled with suspicion; we cannot forgive when unwilling to believe; we cannot trust when filled with doubts.

有力量去愛人或被愛的人都是幸福的人。
Blessed are those who have the ability to love and be loved by others.

問心無愧心最安,能夠付出、助人、救人,最是快樂。
Clear conscience brings peace of mind; the greatest happiness comes from the pleasure of giving and helping others.

有力量幫助他人,是自己的福。
Having the ability to help others is a blessing.

原諒別人就是善待自己。
To forgive others is, in fact, being kind to ourselves.

孝順就是讓父母安心。
Being filial is not making our parents unduly worry about us.

該做的事,排除萬難也要完成;不該做的事,無論任何困難,也要堅持立場。
Do whatever it takes to do what is right. Do whatever it takes to not do what is wrong.

生氣是拿別人的錯誤來懲罰自己。
Being angry is a form of torturing ourselves with the mistakes of others.

人要先點亮自己的心燈,才能引發別人的心燈。
Only when we light up our heart can we inspire others to do the same.

心無邪思,意無邪念,即常可自在。心正則邪不侵。
If our thoughts are upright and wholesome, we can always be at ease and evil cannot come near.

心美看什麼都美。
To a beautiful heart, everything appears beautiful.

人生不怕錯,只怕不改過。
Do not fear making mistakes in life, fear only not correcting them.

李小龍 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.

Absorb what is useful. Discard what is not. Add what is uniquely your own.


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