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Ian Goodfellow

Ian Goodfellow✓ Add us as a preferred source on Google

X @goodfellow_ian
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🔄 Data last refreshed 2 months ago
👤Unclaimed listing

Auto-generated from Ian Goodfellow’s publicly available X info.

Ian Goodfellow hasn’t claimed, verified, or endorsed it, and is not affiliated with, sponsored by, or a partner of SocialDB. Any rates shown are estimates, not set by the creator.

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Followers
378K
Posts
3K
Following
1.4K
Account age
10 yrs
💰 Suggested sponsorship rate
🎁 Free analysisfor Ian Goodfellow
🕵️Fake Followers CheckReal-audience % & bot risk→ 📊Engagement rateBenchmarked vs. peers→ 💰What they chargeFair sponsored-post price→

📊 Post performance

368.3K
Avg views / post
97.4%
Reach vs followers
Sep 2016
On X since

🔥 Top post: When Schmidhuber interrupted my talk on GANs in 2016, he did so · 755.2K views

📊 Activity & format

Posting cadence
0.04 / week
A lower-frequency account — each post lands with more weight.
Content mix
Mostly text
Recent: 1 video · 6 image · 11 text.
Follower / following
277×
Follows 1.4K back. A strong ratio — an audience that follows them, not a follow-for-follow network.
Verification
✓ X Premium
A paid X Premium (Blue) verified account.

Recent posts

View on X ↗
🔥 Top post When Schmidhuber interrupted my talk on GANs in 2016, he did so at the time I was giving credit to relevant prior work: noise contrastive estimation. Schmidhuber isn’t about proper about academic credit assignment, he’s about self-aggrandizement. 755.2K❤ 1.4K🔁 85
More of what my colleagues and I have been working on in AI for fusion is public now 289.2K❤ 2.8K🔁 178 Schmidhuber was a reviewer of the GAN paper in 2014. The reviews are public. He is the reviewer that asked us to cite predictability minimization. He did not ask us to cite artificial creativity (his current complaint). He hadn’t thought o… 368.3K❤ 1.3K🔁 88 Posting a call for help: does anyone know of a good way to simultaneously treat both POTS and Ménière’s disease? Please contact me if you’re either a clinician with experience doing this or a patient who has found a good solution. Context … 370.7K❤ 1.4K🔁 458 I'm excited to announce that I've joined DeepMind! I'll be a research scientist in @OriolVinyalsML 's Deep Learning team. ❤ 6.9K🔁 359 This exciting new PyTorch library includes quite a lot of the GANs I've featured in my talks over the past few years, all in one place! ❤ 2K🔁 415 I’m in Fortune’s 40 under 40: ❤ 1.7K🔁 191 Whoa! It turns out that famous examples of NLP systems succeeding and failing were very misleading. “Man is to king as woman is to queen” only works if the model is hardcoded not to be able to say “king” for the last word. ❤ 1.3K🔁 374 ML Twitter, what are your favorite papers / other resources about the class imbalance problem? ❤ 1.2K🔁 262 OctConv is a simple replacement for the traditional convolution operation that gets better accuracy with fewer FLOPs https://t.co/5CSylHVdA2 ❤ 1.9K🔁 557 4.5 years of GAN progress on face generation. https://t.co/kiQkuYULMC https://t.co/S4aBsU536b https://t.co/8di6K6BxVC https://t.co/UEFhewds2M https://t.co/s6hKQz9gLz ❤ 3.4K🔁 1.3K 4 years of GAN progress (source: https://t.co/hlxW3NnTJP ) ❤ 2.6K🔁 940

💡 Facts

🗓️Joined X in 2016 — 10 years ago.
👁️Averages 368.3K views per post.
📤Posts about 0× per week.
💬0.81% engagement rate.
🏅Earned the 100K Followers for passing 100K followers.

🕵️ Fake follower check

Estimated
69/100
Good Credibility score
85%
Real Real audience
Low Fake-follower risk
High Data confidence
  • Est. 85% real, active audience · Low fake-follower risk.
  • Engagement (~1× of followers engage each post) is around typical for X.
  • Organic base — far more followers than accounts it follows.
  • Verified account.
  • Established account (10+ years old).
  • 0.81% engagement — below the ~2.2% typical for this size.

Heuristic estimate from engagement, follower ratios, account age & growth — a screening signal, not a guarantee.

About

Co-founder of stealth startup. Inventor of GANs. Lead author of http://www.deeplearningbook.org Founding chairman of @pubhealthaction

📸 Gallery

OctConv is a simple replacement for the traditional convolution operation that gets better accuracy with fewer FLOPs https://t.co/5CSylHVdA2 4.5 years of GAN progress on face generation. https://t.co/kiQkuYULMC https://t.co/S4aBsU536b https://t.co/8di6K6BxVC https://t.co/UEFhewds2M https://t.co/s6hKQz9gLz 4 years of GAN progress (source: https://t.co/hlxW3NnTJP ) By looking at this image, you can see how sensitive your own eyes are to contrast at different frequencies (taller apparent peaks=more sensitivity at that frequency). It's like a graph that is made by perceiving the graph itself. h/t @catherineols https://t.co/3WosnCfbX1 One of my favorite samples from the Progressive GANs paper is this one from the "cat" category. Apparently some of the cat training photos were memes with text. The GAN doesn't know what text is so it has made up new text-like imagery in the right place for a meme caption. GANs for generating images of how clothes will fit. Only two of these images are photos. https://t.co/FYCBoveqh9 CycleGAN turning a horse video into a zebra video ( https://t.co/YYCsVt4rIP )

🔀 Audience overlap

Estimated

Estimated shared audience with similar creators — useful for avoiding overlap (or doubling down) when planning a campaign.

Deion | SeeReax Deion | SeeReax 18% Kris Kris 16% Barcelona Barcelona 14% TVガイドWeb【公式】 TVガイドWeb【公式】 14% Serhii Sternenko Serhii Sternenko 12% Thomas Wolf Thomas Wolf 10%

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